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class="vector-toc-list"> <li id="toc-Intrusion_detection_2" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Intrusion_detection_2"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.1</span> <span>Intrusion detection</span> </div> </a> <ul id="toc-Intrusion_detection_2-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Fintech_fraud_detection" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Fintech_fraud_detection"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.2</span> <span>Fintech fraud detection</span> </div> </a> <ul id="toc-Fintech_fraud_detection-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Preprocessing" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Preprocessing"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.3</span> <span>Preprocessing</span> </div> </a> <ul id="toc-Preprocessing-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Video_surveillance" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Video_surveillance"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.4</span> <span>Video surveillance</span> </div> </a> <ul id="toc-Video_surveillance-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-IT_infrastructure" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#IT_infrastructure"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.5</span> <span>IT infrastructure</span> </div> </a> <ul id="toc-IT_infrastructure-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-IoT_systems" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#IoT_systems"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.6</span> <span>IoT systems</span> </div> </a> <ul id="toc-IoT_systems-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Petroleum_industry" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Petroleum_industry"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.7</span> <span>Petroleum industry</span> </div> </a> <ul id="toc-Petroleum_industry-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Oil_and_gas_pipeline_monitoring" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Oil_and_gas_pipeline_monitoring"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.8</span> <span>Oil and gas pipeline monitoring</span> </div> </a> <ul id="toc-Oil_and_gas_pipeline_monitoring-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Methods" class="vector-toc-list-item vector-toc-level-1"> <a class="vector-toc-link" href="#Methods"> <div class="vector-toc-text"> <span class="vector-toc-numb">4</span> <span>Methods</span> </div> </a> <button aria-controls="toc-Methods-sublist" class="cdx-button cdx-button--weight-quiet cdx-button--icon-only vector-toc-toggle"> <span class="vector-icon mw-ui-icon-wikimedia-expand"></span> <span>Toggle Methods subsection</span> </button> <ul id="toc-Methods-sublist" class="vector-toc-list"> <li id="toc-Statistical" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Statistical"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.1</span> <span>Statistical</span> </div> </a> <ul id="toc-Statistical-sublist" class="vector-toc-list"> <li id="toc-Parameter-free" class="vector-toc-list-item vector-toc-level-3"> <a class="vector-toc-link" href="#Parameter-free"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.1.1</span> <span>Parameter-free</span> </div> </a> <ul id="toc-Parameter-free-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Parametric-based" class="vector-toc-list-item vector-toc-level-3"> <a class="vector-toc-link" href="#Parametric-based"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.1.2</span> <span>Parametric-based</span> </div> </a> <ul id="toc-Parametric-based-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Density" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Density"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.2</span> <span>Density</span> </div> </a> <ul id="toc-Density-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Neural_networks" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Neural_networks"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.3</span> <span>Neural networks</span> </div> </a> <ul id="toc-Neural_networks-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Cluster-based" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Cluster-based"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.4</span> <span>Cluster-based</span> </div> </a> <ul id="toc-Cluster-based-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Ensembles" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Ensembles"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.5</span> <span>Ensembles</span> </div> </a> <ul id="toc-Ensembles-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Others" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Others"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.6</span> <span>Others</span> </div> </a> <ul id="toc-Others-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Anomaly_detection_in_dynamic_networks" class="vector-toc-list-item vector-toc-level-1"> <a class="vector-toc-link" href="#Anomaly_detection_in_dynamic_networks"> <div class="vector-toc-text"> <span class="vector-toc-numb">5</span> <span>Anomaly detection in dynamic networks</span> </div> </a> <button aria-controls="toc-Anomaly_detection_in_dynamic_networks-sublist" class="cdx-button cdx-button--weight-quiet cdx-button--icon-only vector-toc-toggle"> <span class="vector-icon mw-ui-icon-wikimedia-expand"></span> <span>Toggle Anomaly detection in dynamic networks subsection</span> </button> <ul id="toc-Anomaly_detection_in_dynamic_networks-sublist" class="vector-toc-list"> <li id="toc-Types_of_anomalies_in_dynamic_networks" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Types_of_anomalies_in_dynamic_networks"> <div class="vector-toc-text"> <span class="vector-toc-numb">5.1</span> <span>Types of anomalies in dynamic networks</span> </div> </a> <ul id="toc-Types_of_anomalies_in_dynamic_networks-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Explainable_anomaly_detection" class="vector-toc-list-item vector-toc-level-1"> <a class="vector-toc-link" href="#Explainable_anomaly_detection"> <div class="vector-toc-text"> <span class="vector-toc-numb">6</span> <span>Explainable anomaly detection</span> </div> </a> <ul id="toc-Explainable_anomaly_detection-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Software" class="vector-toc-list-item vector-toc-level-1"> <a class="vector-toc-link" href="#Software"> <div class="vector-toc-text"> <span class="vector-toc-numb">7</span> <span>Software</span> </div> </a> <ul id="toc-Software-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Datasets" class="vector-toc-list-item vector-toc-level-1"> <a class="vector-toc-link" href="#Datasets"> <div class="vector-toc-text"> <span class="vector-toc-numb">8</span> <span>Datasets</span> </div> </a> <ul id="toc-Datasets-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-See_also" class="vector-toc-list-item vector-toc-level-1"> <a class="vector-toc-link" href="#See_also"> <div class="vector-toc-text"> <span class="vector-toc-numb">9</span> <span>See also</span> </div> </a> <ul id="toc-See_also-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-References" class="vector-toc-list-item vector-toc-level-1"> <a class="vector-toc-link" href="#References"> <div class="vector-toc-text"> <span class="vector-toc-numb">10</span> <span>References</span> </div> </a> <ul id="toc-References-sublist" class="vector-toc-list"> </ul> </li> </ul> </div> </div> </nav> </div> </div> <div class="mw-content-container"> <main id="content" class="mw-body"> <header class="mw-body-header vector-page-titlebar"> <nav aria-label="Contents" class="vector-toc-landmark"> <div id="vector-page-titlebar-toc" class="vector-dropdown vector-page-titlebar-toc vector-button-flush-left" > <input type="checkbox" id="vector-page-titlebar-toc-checkbox" role="button" aria-haspopup="true" data-event-name="ui.dropdown-vector-page-titlebar-toc" class="vector-dropdown-checkbox " aria-label="Toggle the table of contents" > <label id="vector-page-titlebar-toc-label" for="vector-page-titlebar-toc-checkbox" class="vector-dropdown-label cdx-button cdx-button--fake-button cdx-button--fake-button--enabled cdx-button--weight-quiet cdx-button--icon-only " aria-hidden="true" ><span class="vector-icon mw-ui-icon-listBullet mw-ui-icon-wikimedia-listBullet"></span> <span class="vector-dropdown-label-text">Toggle the table of contents</span> </label> <div class="vector-dropdown-content"> <div id="vector-page-titlebar-toc-unpinned-container" class="vector-unpinned-container"> </div> </div> </div> </nav> <h1 id="firstHeading" class="firstHeading mw-first-heading"><span class="mw-page-title-main">Anomaly detection</span></h1> <div id="p-lang-btn" class="vector-dropdown mw-portlet mw-portlet-lang" > <input type="checkbox" id="p-lang-btn-checkbox" role="button" aria-haspopup="true" data-event-name="ui.dropdown-p-lang-btn" class="vector-dropdown-checkbox mw-interlanguage-selector" aria-label="Go to an article in another language. Available in 20 languages" > <label id="p-lang-btn-label" for="p-lang-btn-checkbox" class="vector-dropdown-label cdx-button cdx-button--fake-button cdx-button--fake-button--enabled cdx-button--weight-quiet cdx-button--action-progressive mw-portlet-lang-heading-20" aria-hidden="true" ><span class="vector-icon mw-ui-icon-language-progressive mw-ui-icon-wikimedia-language-progressive"></span> <span class="vector-dropdown-label-text">20 languages</span> </label> <div class="vector-dropdown-content"> <div class="vector-menu-content"> <ul class="vector-menu-content-list"> <li class="interlanguage-link interwiki-ar mw-list-item"><a href="https://ar.wikipedia.org/wiki/%D8%A7%D9%83%D8%AA%D8%B4%D8%A7%D9%81_%D8%A7%D9%84%D8%B4%D8%B0%D9%88%D8%B0" title="اكتشاف الشذوذ – Arabic" lang="ar" hreflang="ar" data-title="اكتشاف الشذوذ" data-language-autonym="العربية" data-language-local-name="Arabic" class="interlanguage-link-target"><span>العربية</span></a></li><li class="interlanguage-link interwiki-bg mw-list-item"><a href="https://bg.wikipedia.org/wiki/%D0%9E%D1%82%D0%BA%D1%80%D0%B8%D0%B2%D0%B0%D0%BD%D0%B5_%D0%BD%D0%B0_%D0%B0%D0%BD%D0%BE%D0%BC%D0%B0%D0%BB%D0%B8%D0%B8" title="Откриване на аномалии – Bulgarian" lang="bg" hreflang="bg" data-title="Откриване на аномалии" data-language-autonym="Български" data-language-local-name="Bulgarian" class="interlanguage-link-target"><span>Български</span></a></li><li class="interlanguage-link interwiki-ca mw-list-item"><a href="https://ca.wikipedia.org/wiki/Detecci%C3%B3_d%27anomalies" title="Detecció d'anomalies – Catalan" lang="ca" hreflang="ca" data-title="Detecció d'anomalies" data-language-autonym="Català" data-language-local-name="Catalan" class="interlanguage-link-target"><span>Català</span></a></li><li class="interlanguage-link interwiki-cs mw-list-item"><a href="https://cs.wikipedia.org/wiki/Detekce_anom%C3%A1li%C3%AD" title="Detekce anomálií – Czech" lang="cs" hreflang="cs" data-title="Detekce anomálií" data-language-autonym="Čeština" data-language-local-name="Czech" class="interlanguage-link-target"><span>Čeština</span></a></li><li class="interlanguage-link interwiki-et mw-list-item"><a href="https://et.wikipedia.org/wiki/Anomaaliate_tuvastamine" title="Anomaaliate tuvastamine – Estonian" lang="et" hreflang="et" data-title="Anomaaliate tuvastamine" data-language-autonym="Eesti" data-language-local-name="Estonian" class="interlanguage-link-target"><span>Eesti</span></a></li><li class="interlanguage-link interwiki-el mw-list-item"><a href="https://el.wikipedia.org/wiki/%CE%91%CE%BD%CE%AF%CF%87%CE%BD%CE%B5%CF%85%CF%83%CE%B7_%CE%B1%CE%BD%CF%89%CE%BC%CE%B1%CE%BB%CE%B9%CF%8E%CE%BD" title="Ανίχνευση ανωμαλιών – Greek" lang="el" hreflang="el" data-title="Ανίχνευση ανωμαλιών" data-language-autonym="Ελληνικά" data-language-local-name="Greek" class="interlanguage-link-target"><span>Ελληνικά</span></a></li><li class="interlanguage-link interwiki-es mw-list-item"><a href="https://es.wikipedia.org/wiki/Detecci%C3%B3n_de_anomal%C3%ADas" title="Detección de anomalías – Spanish" lang="es" hreflang="es" data-title="Detección de anomalías" data-language-autonym="Español" data-language-local-name="Spanish" class="interlanguage-link-target"><span>Español</span></a></li><li class="interlanguage-link interwiki-fa mw-list-item"><a href="https://fa.wikipedia.org/wiki/%D8%B1%D9%88%D8%B4_%D8%AA%D8%B4%D8%AE%DB%8C%D8%B5_%D9%86%D8%A7%D9%87%D9%86%D8%AC%D8%A7%D8%B1%DB%8C" title="روش تشخیص ناهنجاری – Persian" lang="fa" hreflang="fa" data-title="روش تشخیص ناهنجاری" data-language-autonym="فارسی" data-language-local-name="Persian" class="interlanguage-link-target"><span>فارسی</span></a></li><li class="interlanguage-link interwiki-fr mw-list-item"><a href="https://fr.wikipedia.org/wiki/D%C3%A9tection_d%27anomalies" title="Détection d'anomalies – French" lang="fr" hreflang="fr" data-title="Détection d'anomalies" data-language-autonym="Français" data-language-local-name="French" class="interlanguage-link-target"><span>Français</span></a></li><li class="interlanguage-link interwiki-ko mw-list-item"><a href="https://ko.wikipedia.org/wiki/%EC%9D%B4%EC%83%81_%ED%83%90%EC%A7%80" title="이상 탐지 – Korean" lang="ko" hreflang="ko" data-title="이상 탐지" data-language-autonym="한국어" data-language-local-name="Korean" class="interlanguage-link-target"><span>한국어</span></a></li><li class="interlanguage-link interwiki-it mw-list-item"><a href="https://it.wikipedia.org/wiki/Rilevamento_delle_anomalie" title="Rilevamento delle anomalie – Italian" lang="it" hreflang="it" data-title="Rilevamento delle anomalie" data-language-autonym="Italiano" data-language-local-name="Italian" class="interlanguage-link-target"><span>Italiano</span></a></li><li class="interlanguage-link interwiki-he mw-list-item"><a href="https://he.wikipedia.org/wiki/%D7%96%D7%99%D7%94%D7%95%D7%99_%D7%90%D7%A0%D7%95%D7%9E%D7%9C%D7%99%D7%95%D7%AA" title="זיהוי אנומליות – Hebrew" lang="he" hreflang="he" data-title="זיהוי אנומליות" data-language-autonym="עברית" data-language-local-name="Hebrew" class="interlanguage-link-target"><span>עברית</span></a></li><li class="interlanguage-link interwiki-ml mw-list-item"><a href="https://ml.wikipedia.org/wiki/%E0%B4%85%E0%B4%A8%E0%B5%8B%E0%B4%AE%E0%B4%B2%E0%B4%BF_%E0%B4%A1%E0%B4%BF%E0%B4%B1%E0%B5%8D%E0%B4%B1%E0%B4%95%E0%B5%8D%E0%B4%B7%E0%B5%BB" title="അനോമലി ഡിറ്റക്ഷൻ – Malayalam" lang="ml" hreflang="ml" data-title="അനോമലി ഡിറ്റക്ഷൻ" data-language-autonym="മലയാളം" data-language-local-name="Malayalam" class="interlanguage-link-target"><span>മലയാളം</span></a></li><li class="interlanguage-link interwiki-ja mw-list-item"><a href="https://ja.wikipedia.org/wiki/%E7%95%B0%E5%B8%B8%E6%A4%9C%E7%9F%A5" title="異常検知 – Japanese" lang="ja" hreflang="ja" data-title="異常検知" data-language-autonym="日本語" data-language-local-name="Japanese" class="interlanguage-link-target"><span>日本語</span></a></li><li class="interlanguage-link interwiki-pt mw-list-item"><a href="https://pt.wikipedia.org/wiki/Detec%C3%A7%C3%A3o_de_anomalias" title="Detecção de anomalias – Portuguese" lang="pt" hreflang="pt" data-title="Detecção de anomalias" data-language-autonym="Português" data-language-local-name="Portuguese" class="interlanguage-link-target"><span>Português</span></a></li><li class="interlanguage-link interwiki-ru mw-list-item"><a href="https://ru.wikipedia.org/wiki/%D0%92%D1%8B%D1%8F%D0%B2%D0%BB%D0%B5%D0%BD%D0%B8%D0%B5_%D0%B0%D0%BD%D0%BE%D0%BC%D0%B0%D0%BB%D0%B8%D0%B9" title="Выявление аномалий – Russian" lang="ru" hreflang="ru" data-title="Выявление аномалий" data-language-autonym="Русский" data-language-local-name="Russian" class="interlanguage-link-target"><span>Русский</span></a></li><li class="interlanguage-link interwiki-tr mw-list-item"><a href="https://tr.wikipedia.org/wiki/Anomali_tespiti" title="Anomali tespiti – Turkish" lang="tr" hreflang="tr" data-title="Anomali tespiti" data-language-autonym="Türkçe" data-language-local-name="Turkish" class="interlanguage-link-target"><span>Türkçe</span></a></li><li class="interlanguage-link interwiki-uk mw-list-item"><a href="https://uk.wikipedia.org/wiki/%D0%92%D0%B8%D1%8F%D0%B2%D0%BB%D0%B5%D0%BD%D0%BD%D1%8F_%D0%B0%D0%BD%D0%BE%D0%BC%D0%B0%D0%BB%D1%96%D0%B9" title="Виявлення аномалій – Ukrainian" lang="uk" hreflang="uk" data-title="Виявлення аномалій" data-language-autonym="Українська" data-language-local-name="Ukrainian" class="interlanguage-link-target"><span>Українська</span></a></li><li class="interlanguage-link interwiki-zh-yue mw-list-item"><a href="https://zh-yue.wikipedia.org/wiki/%E7%95%B0%E5%B8%B8%E6%AA%A2%E6%B8%AC" title="異常檢測 – Cantonese" lang="yue" hreflang="yue" data-title="異常檢測" data-language-autonym="粵語" data-language-local-name="Cantonese" class="interlanguage-link-target"><span>粵語</span></a></li><li class="interlanguage-link interwiki-zh mw-list-item"><a href="https://zh.wikipedia.org/wiki/%E5%BC%82%E5%B8%B8%E6%A3%80%E6%B5%8B" title="异常检测 – Chinese" lang="zh" hreflang="zh" data-title="异常检测" data-language-autonym="中文" data-language-local-name="Chinese" class="interlanguage-link-target"><span>中文</span></a></li> </ul> <div class="after-portlet after-portlet-lang"><span class="wb-langlinks-edit wb-langlinks-link"><a href="https://www.wikidata.org/wiki/Special:EntityPage/Q3560506#sitelinks-wikipedia" title="Edit interlanguage links" class="wbc-editpage">Edit links</a></span></div> </div> </div> </div> </header> <div class="vector-page-toolbar"> <div class="vector-page-toolbar-container"> <div id="left-navigation"> <nav aria-label="Namespaces"> <div id="p-associated-pages" class="vector-menu vector-menu-tabs mw-portlet mw-portlet-associated-pages" > <div class="vector-menu-content"> <ul class="vector-menu-content-list"> <li id="ca-nstab-main" class="selected vector-tab-noicon mw-list-item"><a href="/wiki/Anomaly_detection" title="View the content page [c]" accesskey="c"><span>Article</span></a></li><li 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a{color:var(--color-progressive)!important}}@media print{body.ns-0 .mw-parser-output .sidebar{display:none!important}}</style><style data-mw-deduplicate="TemplateStyles:r886047488">.mw-parser-output .nobold{font-weight:normal}</style><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r886047488"><table class="sidebar sidebar-collapse nomobile nowraplinks"><tbody><tr><td class="sidebar-pretitle">Part of a series on</td></tr><tr><th class="sidebar-title-with-pretitle"><a href="/wiki/Machine_learning" title="Machine learning">Machine learning</a><br />and <a href="/wiki/Data_mining" title="Data mining">data mining</a></th></tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)">Paradigms</div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Supervised_learning" title="Supervised learning">Supervised learning</a></li> <li><a href="/wiki/Unsupervised_learning" title="Unsupervised learning">Unsupervised learning</a></li> <li><a href="/wiki/Semi-supervised_learning" class="mw-redirect" title="Semi-supervised learning">Semi-supervised learning</a></li> <li><a href="/wiki/Self-supervised_learning" title="Self-supervised learning">Self-supervised learning</a></li> <li><a href="/wiki/Reinforcement_learning" title="Reinforcement learning">Reinforcement learning</a></li> <li><a href="/wiki/Meta-learning_(computer_science)" title="Meta-learning (computer science)">Meta-learning</a></li> <li><a href="/wiki/Online_machine_learning" title="Online machine learning">Online learning</a></li> <li><a href="/wiki/Batch_learning" class="mw-redirect" title="Batch learning">Batch learning</a></li> <li><a href="/wiki/Curriculum_learning" title="Curriculum learning">Curriculum learning</a></li> <li><a href="/wiki/Rule-based_machine_learning" title="Rule-based machine learning">Rule-based learning</a></li> <li><a href="/wiki/Neuro-symbolic_AI" title="Neuro-symbolic AI">Neuro-symbolic AI</a></li> <li><a href="/wiki/Neuromorphic_engineering" class="mw-redirect" title="Neuromorphic engineering">Neuromorphic engineering</a></li> <li><a href="/wiki/Quantum_machine_learning" title="Quantum machine learning">Quantum machine learning</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)">Problems</div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Statistical_classification" title="Statistical classification">Classification</a></li> <li><a href="/wiki/Generative_model" title="Generative model">Generative modeling</a></li> <li><a href="/wiki/Regression_analysis" title="Regression analysis">Regression</a></li> <li><a href="/wiki/Cluster_analysis" title="Cluster analysis">Clustering</a></li> <li><a href="/wiki/Dimensionality_reduction" title="Dimensionality reduction">Dimensionality reduction</a></li> <li><a href="/wiki/Density_estimation" title="Density estimation">Density estimation</a></li> <li><a class="mw-selflink selflink">Anomaly detection</a></li> <li><a href="/wiki/Data_cleaning" class="mw-redirect" title="Data cleaning">Data cleaning</a></li> <li><a href="/wiki/Automated_machine_learning" title="Automated machine learning">AutoML</a></li> <li><a href="/wiki/Association_rule_learning" title="Association rule learning">Association rules</a></li> <li><a href="/wiki/Semantic_analysis_(machine_learning)" title="Semantic analysis (machine learning)">Semantic analysis</a></li> <li><a href="/wiki/Structured_prediction" title="Structured prediction">Structured prediction</a></li> <li><a href="/wiki/Feature_engineering" title="Feature engineering">Feature engineering</a></li> <li><a href="/wiki/Feature_learning" title="Feature learning">Feature learning</a></li> <li><a href="/wiki/Learning_to_rank" title="Learning to rank">Learning to rank</a></li> <li><a href="/wiki/Grammar_induction" title="Grammar induction">Grammar induction</a></li> <li><a href="/wiki/Ontology_learning" title="Ontology learning">Ontology learning</a></li> <li><a href="/wiki/Multimodal_learning" title="Multimodal learning">Multimodal learning</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)"><div style="display: inline-block; line-height: 1.2em; padding: .1em 0;"><a href="/wiki/Supervised_learning" title="Supervised learning">Supervised learning</a><br /><span class="nobold"><span style="font-size:85%;">(<b><a href="/wiki/Statistical_classification" title="Statistical classification">classification</a></b> • <b><a href="/wiki/Regression_analysis" title="Regression analysis">regression</a></b>)</span></span> </div></div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Apprenticeship_learning" title="Apprenticeship learning">Apprenticeship learning</a></li> <li><a href="/wiki/Decision_tree_learning" title="Decision tree learning">Decision trees</a></li> <li><a href="/wiki/Ensemble_learning" title="Ensemble learning">Ensembles</a> <ul><li><a href="/wiki/Bootstrap_aggregating" title="Bootstrap aggregating">Bagging</a></li> <li><a href="/wiki/Boosting_(machine_learning)" title="Boosting (machine learning)">Boosting</a></li> <li><a href="/wiki/Random_forest" title="Random forest">Random forest</a></li></ul></li> <li><a href="/wiki/K-nearest_neighbors_algorithm" title="K-nearest neighbors algorithm"><i>k</i>-NN</a></li> <li><a href="/wiki/Linear_regression" title="Linear regression">Linear regression</a></li> <li><a href="/wiki/Naive_Bayes_classifier" title="Naive Bayes classifier">Naive Bayes</a></li> <li><a href="/wiki/Artificial_neural_network" class="mw-redirect" title="Artificial neural network">Artificial neural networks</a></li> <li><a href="/wiki/Logistic_regression" title="Logistic regression">Logistic regression</a></li> <li><a href="/wiki/Perceptron" title="Perceptron">Perceptron</a></li> <li><a href="/wiki/Relevance_vector_machine" title="Relevance vector machine">Relevance vector machine (RVM)</a></li> <li><a href="/wiki/Support_vector_machine" title="Support vector machine">Support vector machine (SVM)</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)"><a href="/wiki/Cluster_analysis" title="Cluster analysis">Clustering</a></div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/BIRCH" title="BIRCH">BIRCH</a></li> <li><a href="/wiki/CURE_algorithm" title="CURE algorithm">CURE</a></li> <li><a href="/wiki/Hierarchical_clustering" title="Hierarchical clustering">Hierarchical</a></li> <li><a href="/wiki/K-means_clustering" title="K-means clustering"><i>k</i>-means</a></li> <li><a href="/wiki/Fuzzy_clustering" title="Fuzzy clustering">Fuzzy</a></li> <li><a href="/wiki/Expectation%E2%80%93maximization_algorithm" title="Expectation–maximization algorithm">Expectation–maximization (EM)</a></li> <li><br /><a href="/wiki/DBSCAN" title="DBSCAN">DBSCAN</a></li> <li><a href="/wiki/OPTICS_algorithm" title="OPTICS algorithm">OPTICS</a></li> <li><a href="/wiki/Mean_shift" title="Mean shift">Mean shift</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)"><a href="/wiki/Dimensionality_reduction" title="Dimensionality reduction">Dimensionality reduction</a></div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Factor_analysis" title="Factor analysis">Factor analysis</a></li> <li><a href="/wiki/Canonical_correlation" title="Canonical correlation">CCA</a></li> <li><a href="/wiki/Independent_component_analysis" title="Independent component analysis">ICA</a></li> <li><a href="/wiki/Linear_discriminant_analysis" title="Linear discriminant analysis">LDA</a></li> <li><a href="/wiki/Non-negative_matrix_factorization" title="Non-negative matrix factorization">NMF</a></li> <li><a href="/wiki/Principal_component_analysis" title="Principal component analysis">PCA</a></li> <li><a href="/wiki/Proper_generalized_decomposition" title="Proper generalized decomposition">PGD</a></li> <li><a href="/wiki/T-distributed_stochastic_neighbor_embedding" title="T-distributed stochastic neighbor embedding">t-SNE</a></li> <li><a href="/wiki/Sparse_dictionary_learning" title="Sparse dictionary learning">SDL</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)"><a href="/wiki/Structured_prediction" title="Structured prediction">Structured prediction</a></div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Graphical_model" title="Graphical model">Graphical models</a> <ul><li><a href="/wiki/Bayesian_network" title="Bayesian network">Bayes net</a></li> <li><a href="/wiki/Conditional_random_field" title="Conditional random field">Conditional random field</a></li> <li><a href="/wiki/Hidden_Markov_model" title="Hidden Markov model">Hidden Markov</a></li></ul></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)"><a class="mw-selflink selflink">Anomaly detection</a></div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Random_sample_consensus" title="Random sample consensus">RANSAC</a></li> <li><a href="/wiki/K-nearest_neighbors_algorithm" title="K-nearest neighbors algorithm"><i>k</i>-NN</a></li> <li><a href="/wiki/Local_outlier_factor" title="Local outlier factor">Local outlier factor</a></li> <li><a href="/wiki/Isolation_forest" title="Isolation forest">Isolation forest</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)"><a href="/wiki/Artificial_neural_network" class="mw-redirect" title="Artificial neural network">Artificial neural network</a></div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Autoencoder" title="Autoencoder">Autoencoder</a></li> <li><a href="/wiki/Deep_learning" title="Deep learning">Deep learning</a></li> <li><a href="/wiki/Feedforward_neural_network" title="Feedforward neural network">Feedforward neural network</a></li> <li><a href="/wiki/Recurrent_neural_network" title="Recurrent neural network">Recurrent neural network</a> <ul><li><a href="/wiki/Long_short-term_memory" title="Long short-term memory">LSTM</a></li> <li><a href="/wiki/Gated_recurrent_unit" title="Gated recurrent unit">GRU</a></li> <li><a href="/wiki/Echo_state_network" title="Echo state network">ESN</a></li> <li><a href="/wiki/Reservoir_computing" title="Reservoir computing">reservoir computing</a></li></ul></li> <li><a href="/wiki/Boltzmann_machine" title="Boltzmann machine">Boltzmann machine</a> <ul><li><a href="/wiki/Restricted_Boltzmann_machine" title="Restricted Boltzmann machine">Restricted</a></li></ul></li> <li><a href="/wiki/Generative_adversarial_network" title="Generative adversarial network">GAN</a></li> <li><a href="/wiki/Diffusion_model" title="Diffusion model">Diffusion model</a></li> <li><a href="/wiki/Self-organizing_map" title="Self-organizing map">SOM</a></li> <li><a href="/wiki/Convolutional_neural_network" title="Convolutional neural network">Convolutional neural network</a> <ul><li><a href="/wiki/U-Net" title="U-Net">U-Net</a></li> <li><a href="/wiki/LeNet" title="LeNet">LeNet</a></li> <li><a href="/wiki/AlexNet" title="AlexNet">AlexNet</a></li> <li><a href="/wiki/DeepDream" title="DeepDream">DeepDream</a></li></ul></li> <li><a href="/wiki/Neural_radiance_field" title="Neural radiance field">Neural radiance field</a></li> <li><a href="/wiki/Transformer_(machine_learning_model)" class="mw-redirect" title="Transformer (machine learning model)">Transformer</a> <ul><li><a href="/wiki/Vision_transformer" title="Vision transformer">Vision</a></li></ul></li> <li><a href="/wiki/Mamba_(deep_learning_architecture)" title="Mamba (deep learning architecture)">Mamba</a></li> <li><a href="/wiki/Spiking_neural_network" title="Spiking neural network">Spiking neural network</a></li> <li><a href="/wiki/Memtransistor" title="Memtransistor">Memtransistor</a></li> <li><a href="/wiki/Electrochemical_RAM" title="Electrochemical RAM">Electrochemical RAM</a> (ECRAM)</li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)"><a href="/wiki/Reinforcement_learning" title="Reinforcement learning">Reinforcement learning</a></div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Q-learning" title="Q-learning">Q-learning</a></li> <li><a href="/wiki/State%E2%80%93action%E2%80%93reward%E2%80%93state%E2%80%93action" title="State–action–reward–state–action">SARSA</a></li> <li><a href="/wiki/Temporal_difference_learning" title="Temporal difference learning">Temporal difference (TD)</a></li> <li><a href="/wiki/Multi-agent_reinforcement_learning" title="Multi-agent reinforcement learning">Multi-agent</a> <ul><li><a href="/wiki/Self-play_(reinforcement_learning_technique)" class="mw-redirect" title="Self-play (reinforcement learning technique)">Self-play</a></li></ul></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)">Learning with humans</div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Active_learning_(machine_learning)" title="Active learning (machine learning)">Active learning</a></li> <li><a href="/wiki/Crowdsourcing" title="Crowdsourcing">Crowdsourcing</a></li> <li><a href="/wiki/Human-in-the-loop" title="Human-in-the-loop">Human-in-the-loop</a></li> <li><a href="/wiki/Reinforcement_learning_from_human_feedback" title="Reinforcement learning from human feedback">RLHF</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)">Model diagnostics</div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Coefficient_of_determination" title="Coefficient of determination">Coefficient of determination</a></li> <li><a href="/wiki/Confusion_matrix" title="Confusion matrix">Confusion matrix</a></li> <li><a href="/wiki/Learning_curve_(machine_learning)" title="Learning curve (machine learning)">Learning curve</a></li> <li><a href="/wiki/Receiver_operating_characteristic" title="Receiver operating characteristic">ROC curve</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)">Mathematical foundations</div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Kernel_machines" class="mw-redirect" title="Kernel machines">Kernel machines</a></li> <li><a href="/wiki/Bias%E2%80%93variance_tradeoff" title="Bias–variance tradeoff">Bias–variance tradeoff</a></li> <li><a href="/wiki/Computational_learning_theory" title="Computational learning theory">Computational learning theory</a></li> <li><a href="/wiki/Empirical_risk_minimization" title="Empirical risk minimization">Empirical risk minimization</a></li> <li><a href="/wiki/Occam_learning" title="Occam learning">Occam learning</a></li> <li><a href="/wiki/Probably_approximately_correct_learning" title="Probably approximately correct learning">PAC learning</a></li> <li><a href="/wiki/Statistical_learning_theory" title="Statistical learning theory">Statistical learning</a></li> <li><a href="/wiki/Vapnik%E2%80%93Chervonenkis_theory" title="Vapnik–Chervonenkis theory">VC theory</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)">Journals and conferences</div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/ECML_PKDD" title="ECML PKDD">ECML PKDD</a></li> <li><a href="/wiki/Conference_on_Neural_Information_Processing_Systems" title="Conference on Neural Information Processing Systems">NeurIPS</a></li> <li><a href="/wiki/International_Conference_on_Machine_Learning" title="International Conference on Machine Learning">ICML</a></li> <li><a href="/wiki/International_Conference_on_Learning_Representations" title="International Conference on Learning Representations">ICLR</a></li> <li><a href="/wiki/International_Joint_Conference_on_Artificial_Intelligence" title="International Joint Conference on Artificial Intelligence">IJCAI</a></li> <li><a href="/wiki/Machine_Learning_(journal)" title="Machine Learning (journal)">ML</a></li> <li><a href="/wiki/Journal_of_Machine_Learning_Research" title="Journal of Machine Learning Research">JMLR</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed machine-learning-list-title"><div class="sidebar-list-title" style="border-top:1px solid #aaa; text-align:center;;color: var(--color-base)">Related articles</div><div class="sidebar-list-content mw-collapsible-content hlist"> <ul><li><a href="/wiki/Glossary_of_artificial_intelligence" title="Glossary of artificial intelligence">Glossary of artificial intelligence</a></li> <li><a href="/wiki/List_of_datasets_for_machine-learning_research" title="List of datasets for machine-learning research">List of datasets for machine-learning research</a> <ul><li><a href="/wiki/List_of_datasets_in_computer_vision_and_image_processing" title="List of datasets in computer vision and image processing">List of datasets in computer vision and image processing</a></li></ul></li> <li><a href="/wiki/Outline_of_machine_learning" title="Outline of machine learning">Outline of machine learning</a></li></ul></div></div></td> </tr><tr><td class="sidebar-navbar"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1129693374"><style data-mw-deduplicate="TemplateStyles:r1239400231">.mw-parser-output .navbar{display:inline;font-size:88%;font-weight:normal}.mw-parser-output .navbar-collapse{float:left;text-align:left}.mw-parser-output .navbar-boxtext{word-spacing:0}.mw-parser-output .navbar ul{display:inline-block;white-space:nowrap;line-height:inherit}.mw-parser-output .navbar-brackets::before{margin-right:-0.125em;content:"[ "}.mw-parser-output .navbar-brackets::after{margin-left:-0.125em;content:" ]"}.mw-parser-output .navbar li{word-spacing:-0.125em}.mw-parser-output .navbar a>span,.mw-parser-output .navbar a>abbr{text-decoration:inherit}.mw-parser-output .navbar-mini abbr{font-variant:small-caps;border-bottom:none;text-decoration:none;cursor:inherit}.mw-parser-output .navbar-ct-full{font-size:114%;margin:0 7em}.mw-parser-output .navbar-ct-mini{font-size:114%;margin:0 4em}html.skin-theme-clientpref-night .mw-parser-output .navbar li a abbr{color:var(--color-base)!important}@media(prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .navbar li a abbr{color:var(--color-base)!important}}@media print{.mw-parser-output .navbar{display:none!important}}</style><div class="navbar plainlinks hlist navbar-mini"><ul><li class="nv-view"><a href="/wiki/Template:Machine_learning" title="Template:Machine learning"><abbr title="View this template">v</abbr></a></li><li class="nv-talk"><a href="/wiki/Template_talk:Machine_learning" title="Template talk:Machine learning"><abbr title="Discuss this template">t</abbr></a></li><li class="nv-edit"><a href="/wiki/Special:EditPage/Template:Machine_learning" title="Special:EditPage/Template:Machine learning"><abbr title="Edit this template">e</abbr></a></li></ul></div></td></tr></tbody></table> <p>In <a href="/wiki/Data_analysis" title="Data analysis">data analysis</a>, <b>anomaly detection</b> (also referred to as <b>outlier detection</b> and sometimes as <b>novelty detection</b>) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior.<sup id="cite_ref-ChandolaSurvey_1-0" class="reference"><a href="#cite_note-ChandolaSurvey-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> Such examples may arouse suspicions of being generated by a different mechanism,<sup id="cite_ref-Hawkins_1980_2-0" class="reference"><a href="#cite_note-Hawkins_1980-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> or appear inconsistent with the remainder of that set of data.<sup id="cite_ref-Outliers_in_statistical_data_3-0" class="reference"><a href="#cite_note-Outliers_in_statistical_data-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> </p><p>Anomaly detection finds application in many domains including <a href="/wiki/Computer_security" title="Computer security">cybersecurity</a>, <a href="/wiki/Medicine" title="Medicine">medicine</a>, <a href="/wiki/Machine_vision" title="Machine vision">machine vision</a>, <a href="/wiki/Statistics" title="Statistics">statistics</a>, <a href="/wiki/Neuroscience" title="Neuroscience">neuroscience</a>, <a href="/wiki/Law_enforcement" title="Law enforcement">law enforcement</a> and <a href="/wiki/Fraud" title="Fraud">financial fraud</a> to name only a few. Anomalies were initially searched for clear rejection or omission from the data to aid statistical analysis, for example to compute the mean or standard deviation. They were also removed to better predictions from models such as linear regression, and more recently their removal aids the performance of machine learning algorithms. However, in many applications anomalies themselves are of interest and are the observations most desirous in the entire data set, which need to be identified and separated from noise or irrelevant outliers. </p><p>Three broad categories of anomaly detection techniques exist.<sup id="cite_ref-ChandolaSurvey_1-1" class="reference"><a href="#cite_note-ChandolaSurvey-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> <b>Supervised anomaly detection</b> techniques require a data set that has been labeled as "normal" and "abnormal" and involves training a classifier. However, this approach is rarely used in anomaly detection due to the general unavailability of labelled data and the inherent unbalanced nature of the classes. <b>Semi-supervised anomaly detection</b> techniques assume that some portion of the data is labelled. This may be any combination of the normal or anomalous data, but more often than not, the techniques construct a model representing <a href="/wiki/Normal_behavior" class="mw-redirect" title="Normal behavior">normal behavior</a> from a given <i>normal</i> training data set, and then test the likelihood of a test instance to be generated by the model. <b>Unsupervised anomaly detection</b> techniques assume the data is unlabelled and are by far the most commonly used due to their wider and relevant application. </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="Definition">Definition</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=1" title="Edit section: Definition"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Many attempts have been made in the statistical and computer science communities to define an anomaly. The most prevalent ones include the following, and can be categorised into three groups: those that are ambiguous, those that are specific to a method with pre-defined thresholds usually chosen empirically, and those that are formally defined: </p> <div class="mw-heading mw-heading3"><h3 id="Ill_defined">Ill defined</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=2" title="Edit section: Ill defined"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li>An outlier is an observation which deviates so much from the other observations as to arouse suspicions that it was generated by a different mechanism.<sup id="cite_ref-Hawkins_1980_2-1" class="reference"><a href="#cite_note-Hawkins_1980-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup></li> <li>Anomalies are instances or collections of data that occur very rarely in the data set and whose features differ significantly from most of the data.</li> <li>An outlier is an observation (or subset of observations) which appears to be inconsistent with the remainder of that set of data.<sup id="cite_ref-Outliers_in_statistical_data_3-1" class="reference"><a href="#cite_note-Outliers_in_statistical_data-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup></li> <li>An anomaly is a point or collection of points that is relatively distant from other points in multi-dimensional space of features.</li> <li>Anomalies are patterns in data that do not conform to a well-defined notion of normal behaviour.<sup id="cite_ref-ChandolaSurvey_1-2" class="reference"><a href="#cite_note-ChandolaSurvey-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup></li></ul> <div class="mw-heading mw-heading3"><h3 id="Specific">Specific</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=3" title="Edit section: Specific"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li>Let T be observations from a univariate Gaussian distribution and O a point from T. Then the z-score for O is greater than a pre-selected threshold if and only if O is an outlier.</li></ul> <div class="mw-heading mw-heading2"><h2 id="History">History</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=4" title="Edit section: History"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <div class="mw-heading mw-heading3"><h3 id="Intrusion_detection">Intrusion detection</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=5" title="Edit section: Intrusion detection"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The concept of intrusion detection, a critical component of anomaly detection, has evolved significantly over time. Initially, it was a manual process where system administrators would monitor for unusual activities, such as a vacationing user's account being accessed or unexpected printer activity. This approach was not scalable and was soon superseded by the analysis of audit logs and system logs for signs of malicious behavior.<sup id="cite_ref-Kemmerer-2002_4-0" class="reference"><a href="#cite_note-Kemmerer-2002-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> </p><p>By the late 1970s and early 1980s, the analysis of these logs was primarily used retrospectively to investigate incidents, as the volume of data made it impractical for real-time monitoring. The affordability of digital storage eventually led to audit logs being analyzed online, with specialized programs being developed to sift through the data. These programs, however, were typically run during off-peak hours due to their computational intensity.<sup id="cite_ref-Kemmerer-2002_4-1" class="reference"><a href="#cite_note-Kemmerer-2002-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> </p><p>The 1990s brought the advent of real-time intrusion detection systems capable of analyzing audit data as it was generated, allowing for immediate detection of and response to attacks. This marked a significant shift towards proactive intrusion detection.<sup id="cite_ref-Kemmerer-2002_4-2" class="reference"><a href="#cite_note-Kemmerer-2002-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> </p><p>As the field has continued to develop, the focus has shifted to creating solutions that can be efficiently implemented across large and complex network environments, adapting to the ever-growing variety of security threats and the dynamic nature of modern computing infrastructures.<sup id="cite_ref-Kemmerer-2002_4-3" class="reference"><a href="#cite_note-Kemmerer-2002-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Applications">Applications</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=6" title="Edit section: Applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Anomaly detection is applicable in a very large number and variety of domains, and is an important subarea of unsupervised machine learning. As such it has applications in cyber-security, <a href="/wiki/Intrusion_detection" class="mw-redirect" title="Intrusion detection">intrusion detection</a>, <a href="/wiki/Fraud_detection" class="mw-redirect" title="Fraud detection">fraud detection</a>, fault detection, system health monitoring, event detection in sensor networks, detecting ecosystem disturbances, defect detection in images using <a href="/wiki/Machine_vision" title="Machine vision">machine vision</a>, medical diagnosis and law enforcement.<sup id="cite_ref-5" class="reference"><a href="#cite_note-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Intrusion_detection_2">Intrusion detection</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=7" title="Edit section: Intrusion detection"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Anomaly detection was proposed for <a href="/wiki/Intrusion_detection_systems" class="mw-redirect" title="Intrusion detection systems">intrusion detection systems</a> (IDS) by <a href="/wiki/Dorothy_E._Denning" title="Dorothy E. Denning">Dorothy Denning</a> in 1986.<sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup> Anomaly detection for IDS is normally accomplished with thresholds and statistics, but can also be done with <a href="/wiki/Soft_computing" title="Soft computing">soft computing</a>, and inductive learning.<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> Types of features proposed by 1999 included profiles of users, workstations, networks, remote hosts, groups of users, and programs based on frequencies, means, variances, covariances, and standard deviations.<sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> The counterpart of anomaly detection in <a href="/wiki/Intrusion_detection" class="mw-redirect" title="Intrusion detection">intrusion detection</a> is <a href="/wiki/Misuse_detection" title="Misuse detection">misuse detection</a>. </p> <div class="mw-heading mw-heading3"><h3 id="Fintech_fraud_detection">Fintech fraud detection</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=8" title="Edit section: Fintech fraud detection"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Anomaly detection is vital in <a href="/wiki/Fintech" title="Fintech">fintech</a> for <a href="/wiki/Fraud" title="Fraud">fraud</a> prevention.<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Preprocessing">Preprocessing</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=9" title="Edit section: Preprocessing"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p><a href="/wiki/Data_pre-processing" class="mw-redirect" title="Data pre-processing">Preprocessing</a> data to remove anomalies can be an important step in data analysis, and is done for a number of reasons. Statistics such as the mean and standard deviation are more accurate after the removal of anomalies, and the visualisation of data can also be improved. In <a href="/wiki/Supervised_learning" title="Supervised learning">supervised learning</a>, removing the anomalous data from the dataset often results in a statistically significant increase in accuracy.<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Video_surveillance">Video surveillance</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=10" title="Edit section: Video surveillance"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Anomaly detection has become increasingly vital in video surveillance to enhance security and safety.<sup id="cite_ref-Qasim-2023_13-0" class="reference"><a href="#cite_note-Qasim-2023-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-14" class="reference"><a href="#cite_note-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup> With the advent of deep learning technologies, methods using Convolutional Neural Networks (CNNs) and Simple Recurrent Units (SRUs) have shown significant promise in identifying unusual activities or behaviors in video data.<sup id="cite_ref-Qasim-2023_13-1" class="reference"><a href="#cite_note-Qasim-2023-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> These models can process and analyze extensive video feeds in real-time, recognizing patterns that deviate from the norm, which may indicate potential security threats or safety violations.<sup id="cite_ref-Qasim-2023_13-2" class="reference"><a href="#cite_note-Qasim-2023-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="IT_infrastructure">IT infrastructure</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=11" title="Edit section: IT infrastructure"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>In <a href="/wiki/IT_infrastructure" title="IT infrastructure">IT infrastructure</a> management, anomaly detection is crucial for ensuring the smooth operation and reliability of services.<sup id="cite_ref-Gow-2018_15-0" class="reference"><a href="#cite_note-Gow-2018-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup> Techniques like the IT Infrastructure Library (ITIL) and monitoring frameworks are employed to track and manage system performance and user experience.<sup id="cite_ref-Gow-2018_15-1" class="reference"><a href="#cite_note-Gow-2018-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup> Detection anomalies can help identify and pre-empt potential performance degradations or system failures, thus maintaining productivity and business process effectiveness.<sup id="cite_ref-Gow-2018_15-2" class="reference"><a href="#cite_note-Gow-2018-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="IoT_systems">IoT systems</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=12" title="Edit section: IoT systems"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Anomaly detection is critical for the security and efficiency of Internet of Things (IoT) systems.<sup id="cite_ref-Chatterjee-2022_16-0" class="reference"><a href="#cite_note-Chatterjee-2022-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> It helps in identifying system failures and security breaches in complex networks of IoT devices.<sup id="cite_ref-Chatterjee-2022_16-1" class="reference"><a href="#cite_note-Chatterjee-2022-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> The methods must manage real-time data, diverse device types, and scale effectively. Garbe et al.<sup id="cite_ref-Garg-2020_17-0" class="reference"><a href="#cite_note-Garg-2020-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup> have introduced a multi-stage anomaly detection framework that improves upon traditional methods by incorporating spatial clustering, density-based clustering, and locality-sensitive hashing. This tailored approach is designed to better handle the vast and varied nature of IoT data, thereby enhancing security and operational reliability in smart infrastructure and industrial IoT systems.<sup id="cite_ref-Garg-2020_17-1" class="reference"><a href="#cite_note-Garg-2020-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Petroleum_industry">Petroleum industry</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=13" title="Edit section: Petroleum industry"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Anomaly detection is crucial in the <a href="/wiki/Petroleum_industry" title="Petroleum industry">petroleum industry</a> for monitoring critical machinery.<sup id="cite_ref-Martí-2015_18-0" class="reference"><a href="#cite_note-Martí-2015-18"><span class="cite-bracket">[</span>18<span class="cite-bracket">]</span></a></sup> Martí et al. used a novel segmentation algorithm to analyze sensor data for real-time anomaly detection.<sup id="cite_ref-Martí-2015_18-1" class="reference"><a href="#cite_note-Martí-2015-18"><span class="cite-bracket">[</span>18<span class="cite-bracket">]</span></a></sup> This approach helps promptly identify and address any irregularities in sensor readings, ensuring the reliability and safety of petroleum operations.<sup id="cite_ref-Martí-2015_18-2" class="reference"><a href="#cite_note-Martí-2015-18"><span class="cite-bracket">[</span>18<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Oil_and_gas_pipeline_monitoring">Oil and gas pipeline monitoring</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=14" title="Edit section: Oil and gas pipeline monitoring"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>In the oil and gas sector, anomaly detection is not just crucial for maintenance and safety, but also for environmental protection.<sup id="cite_ref-Aljameel-2022_19-0" class="reference"><a href="#cite_note-Aljameel-2022-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup> Aljameel et al. propose an advanced machine learning-based model for detecting minor leaks in oil and gas pipelines, a task traditional methods may miss.<sup id="cite_ref-Aljameel-2022_19-1" class="reference"><a href="#cite_note-Aljameel-2022-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Methods">Methods</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=15" title="Edit section: Methods"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Many anomaly detection techniques have been proposed in literature.<sup id="cite_ref-ChandolaSurvey_1-3" class="reference"><a href="#cite_note-ChandolaSurvey-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-ZimekFilzmoser2018_20-0" class="reference"><a href="#cite_note-ZimekFilzmoser2018-20"><span class="cite-bracket">[</span>20<span class="cite-bracket">]</span></a></sup> The performance of methods usually depend on the data sets. For example, some may be suited to detecting local outliers, while others global, and methods have little systematic advantages over another when compared across many data sets.<sup id="cite_ref-CamposZimek2016_21-0" class="reference"><a href="#cite_note-CamposZimek2016-21"><span class="cite-bracket">[</span>21<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-22" class="reference"><a href="#cite_note-22"><span class="cite-bracket">[</span>22<span class="cite-bracket">]</span></a></sup> Almost all algorithms also require the setting of non-intuitive parameters critical for performance, and usually unknown before application. Some of the popular techniques are mentioned below and are broken down into categories: </p> <div class="mw-heading mw-heading3"><h3 id="Statistical">Statistical</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=16" title="Edit section: Statistical"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <div class="mw-heading mw-heading4"><h4 id="Parameter-free">Parameter-free</h4><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=17" title="Edit section: Parameter-free"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1251242444">.mw-parser-output .ambox{border:1px solid #a2a9b1;border-left:10px solid #36c;background-color:#fbfbfb;box-sizing:border-box}.mw-parser-output .ambox+link+.ambox,.mw-parser-output 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//upload.wikimedia.org/wikipedia/commons/thumb/1/1c/Wiki_letter_w_cropped.svg/40px-Wiki_letter_w_cropped.svg.png 2x" data-file-width="44" data-file-height="31" /></a></span></td><td class="mbox-text"><div class="mbox-text-span"><b>This section is empty.</b> You can help by <a class="external text" href="https://en.wikipedia.org/w/index.php?title=Anomaly_detection&action=edit&section=">adding to it</a>. <span class="date-container"><i>(<span class="date">January 2024</span>)</i></span></div></td></tr></tbody></table> <div class="mw-heading mw-heading4"><h4 id="Parametric-based">Parametric-based</h4><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=18" title="Edit section: Parametric-based"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Standard_score" title="Standard score">Z-score</a>,</li> <li><a href="/wiki/Tukey%27s_range_test" title="Tukey's range test">Tukey's range test</a></li> <li><a href="/wiki/Grubbs%27s_test" title="Grubbs's test">Grubbs's test</a></li></ul> <div class="mw-heading mw-heading3"><h3 id="Density">Density</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=19" title="Edit section: Density"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li>Density-based techniques (<a href="/wiki/K-nearest_neighbor_algorithm" class="mw-redirect" title="K-nearest neighbor algorithm">k-nearest neighbor</a>,<sup id="cite_ref-23" class="reference"><a href="#cite_note-23"><span class="cite-bracket">[</span>23<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-24" class="reference"><a href="#cite_note-24"><span class="cite-bracket">[</span>24<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-25" class="reference"><a href="#cite_note-25"><span class="cite-bracket">[</span>25<span class="cite-bracket">]</span></a></sup> <a href="/wiki/Local_outlier_factor" title="Local outlier factor">local outlier factor</a>,<sup id="cite_ref-26" class="reference"><a href="#cite_note-26"><span class="cite-bracket">[</span>26<span class="cite-bracket">]</span></a></sup> <a href="/wiki/Isolation_forest" title="Isolation forest">isolation forests</a>,<sup id="cite_ref-27" class="reference"><a href="#cite_note-27"><span class="cite-bracket">[</span>27<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-28" class="reference"><a href="#cite_note-28"><span class="cite-bracket">[</span>28<span class="cite-bracket">]</span></a></sup> and many more variations of this concept<sup id="cite_ref-29" class="reference"><a href="#cite_note-29"><span class="cite-bracket">[</span>29<span class="cite-bracket">]</span></a></sup>)</li> <li>Subspace-base (SOD),<sup id="cite_ref-Kriegel-2009_30-0" class="reference"><a href="#cite_note-Kriegel-2009-30"><span class="cite-bracket">[</span>30<span class="cite-bracket">]</span></a></sup> correlation-based (COP)<sup id="cite_ref-Kriegel-2012_31-0" class="reference"><a href="#cite_note-Kriegel-2012-31"><span class="cite-bracket">[</span>31<span class="cite-bracket">]</span></a></sup> and tensor-based<sup id="cite_ref-32" class="reference"><a href="#cite_note-32"><span class="cite-bracket">[</span>32<span class="cite-bracket">]</span></a></sup> outlier detection for high-dimensional data<sup id="cite_ref-33" class="reference"><a href="#cite_note-33"><span class="cite-bracket">[</span>33<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/One-class_classification" title="One-class classification">One-class</a> <a href="/wiki/Support_vector_machines" class="mw-redirect" title="Support vector machines">support vector machines</a><sup id="cite_ref-34" class="reference"><a href="#cite_note-34"><span class="cite-bracket">[</span>34<span class="cite-bracket">]</span></a></sup> (OCSVM, SVDD)</li></ul> <div class="mw-heading mw-heading3"><h3 id="Neural_networks">Neural networks</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=20" title="Edit section: Neural networks"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li>Replicator <a href="/wiki/Neural_network" title="Neural network">neural networks</a>,<sup id="cite_ref-replicator_35-0" class="reference"><a href="#cite_note-replicator-35"><span class="cite-bracket">[</span>35<span class="cite-bracket">]</span></a></sup> <a href="/wiki/Autoencoder#Anomaly_detection" title="Autoencoder">autoencoders</a>, variational autoencoders,<sup id="cite_ref-36" class="reference"><a href="#cite_note-36"><span class="cite-bracket">[</span>36<span class="cite-bracket">]</span></a></sup> <a href="/wiki/Long_short-term_memory" title="Long short-term memory">long short-term memory</a> neural networks<sup id="cite_ref-37" class="reference"><a href="#cite_note-37"><span class="cite-bracket">[</span>37<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Bayesian_network" title="Bayesian network">Bayesian networks</a><sup id="cite_ref-replicator_35-1" class="reference"><a href="#cite_note-replicator-35"><span class="cite-bracket">[</span>35<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Hidden_Markov_model" title="Hidden Markov model">Hidden Markov models</a> (HMMs)<sup id="cite_ref-replicator_35-2" class="reference"><a href="#cite_note-replicator-35"><span class="cite-bracket">[</span>35<span class="cite-bracket">]</span></a></sup></li> <li>Minimum Covariance Determinant<sup id="cite_ref-38" class="reference"><a href="#cite_note-38"><span class="cite-bracket">[</span>38<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-39" class="reference"><a href="#cite_note-39"><span class="cite-bracket">[</span>39<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Deep_learning" title="Deep learning">Deep Learning</a><sup id="cite_ref-Qasim-2023_13-3" class="reference"><a href="#cite_note-Qasim-2023-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> <ul><li><b><a href="/wiki/Convolutional_neural_network" title="Convolutional neural network">Convolutional Neural Networks</a> (CNNs):</b> CNNs have shown exceptional performance in the unsupervised learning domain for anomaly detection, especially in image and video data analysis.<sup id="cite_ref-Qasim-2023_13-4" class="reference"><a href="#cite_note-Qasim-2023-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> Their ability to automatically and hierarchically learn spatial hierarchies of features from low to high-level patterns makes them particularly suited for detecting visual anomalies. For instance, CNNs can be trained on image datasets to identify atypical patterns indicative of defects or out-of-norm conditions in industrial quality control scenarios.<sup id="cite_ref-40" class="reference"><a href="#cite_note-40"><span class="cite-bracket">[</span>40<span class="cite-bracket">]</span></a></sup></li> <li><b>Simple Recurrent Units (SRUs):</b> In time-series data, SRUs, a type of recurrent neural network, have been effectively used for anomaly detection by capturing temporal dependencies and sequence anomalies.<sup id="cite_ref-Qasim-2023_13-5" class="reference"><a href="#cite_note-Qasim-2023-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> Unlike traditional RNNs, SRUs are designed to be faster and more parallelizable, offering a better fit for real-time anomaly detection in complex systems such as dynamic financial markets or predictive maintenance in machinery, where identifying temporal irregularities promptly is crucial.<sup id="cite_ref-41" class="reference"><a href="#cite_note-41"><span class="cite-bracket">[</span>41<span class="cite-bracket">]</span></a></sup></li></ul></li></ul> <div class="mw-heading mw-heading3"><h3 id="Cluster-based">Cluster-based</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=21" title="Edit section: Cluster-based"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li>Clustering: <a href="/wiki/Cluster_analysis" title="Cluster analysis">Cluster analysis</a>-based outlier detection<sup id="cite_ref-42" class="reference"><a href="#cite_note-42"><span class="cite-bracket">[</span>42<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-43" class="reference"><a href="#cite_note-43"><span class="cite-bracket">[</span>43<span class="cite-bracket">]</span></a></sup></li> <li>Deviations from <a href="/wiki/Association_rule_learning" title="Association rule learning">association rules</a> and frequent itemsets</li> <li>Fuzzy logic-based outlier detection</li></ul> <div class="mw-heading mw-heading3"><h3 id="Ensembles">Ensembles</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=22" title="Edit section: Ensembles"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Ensemble_learning" title="Ensemble learning">Ensemble techniques</a>, using <a href="/wiki/Random_subspace_method" title="Random subspace method">feature bagging</a>,<sup id="cite_ref-44" class="reference"><a href="#cite_note-44"><span class="cite-bracket">[</span>44<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-45" class="reference"><a href="#cite_note-45"><span class="cite-bracket">[</span>45<span class="cite-bracket">]</span></a></sup> score normalization<sup id="cite_ref-46" class="reference"><a href="#cite_note-46"><span class="cite-bracket">[</span>46<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-47" class="reference"><a href="#cite_note-47"><span class="cite-bracket">[</span>47<span class="cite-bracket">]</span></a></sup> and different sources of diversity<sup id="cite_ref-48" class="reference"><a href="#cite_note-48"><span class="cite-bracket">[</span>48<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-49" class="reference"><a href="#cite_note-49"><span class="cite-bracket">[</span>49<span class="cite-bracket">]</span></a></sup></li></ul> <div class="mw-heading mw-heading3"><h3 id="Others">Others</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=23" title="Edit section: Others"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Histogram-based Outlier Score (HBOS) uses value histograms and assumes feature independence for fast predictions.<sup id="cite_ref-50" class="reference"><a href="#cite_note-50"><span class="cite-bracket">[</span>50<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Anomaly_detection_in_dynamic_networks">Anomaly detection in dynamic networks</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=24" title="Edit section: Anomaly detection in dynamic networks"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Dynamic networks, such as those representing financial systems, social media interactions, and transportation infrastructure, are subject to constant change, making anomaly detection within them a complex task. Unlike static graphs, dynamic networks reflect evolving relationships and states, requiring adaptive techniques for anomaly detection. </p> <div class="mw-heading mw-heading3"><h3 id="Types_of_anomalies_in_dynamic_networks">Types of anomalies in dynamic networks</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=25" title="Edit section: Types of anomalies in dynamic networks"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ol><li>Community anomalies</li> <li>Compression anomalies</li> <li>Decomposition anomalies</li> <li>Distance anomalies</li> <li>Probabilistic model anomalies</li></ol> <div class="mw-heading mw-heading2"><h2 id="Explainable_anomaly_detection">Explainable anomaly detection</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=26" title="Edit section: Explainable anomaly detection"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Many of the methods discussed above only yield an anomaly score prediction, which often can be explained to users as the point being in a region of low data density (or relatively low density compared to the neighbor's densities). In <a href="/wiki/Explainable_artificial_intelligence" title="Explainable artificial intelligence">explainable artificial intelligence</a>, the users demand methods with higher explainability. Some methods allow for more detailed explanations: </p> <ul><li>The Subspace Outlier Degree (SOD)<sup id="cite_ref-Kriegel-2009_30-1" class="reference"><a href="#cite_note-Kriegel-2009-30"><span class="cite-bracket">[</span>30<span class="cite-bracket">]</span></a></sup> identifies attributes where a sample is normal, and attributes in which the sample deviates from the expected.</li> <li>Correlation Outlier Probabilities (COP)<sup id="cite_ref-Kriegel-2012_31-1" class="reference"><a href="#cite_note-Kriegel-2012-31"><span class="cite-bracket">[</span>31<span class="cite-bracket">]</span></a></sup> compute an error vector of how a sample point deviates from an expected location, which can be interpreted as a counterfactual explanation: the sample would be normal if it were moved to that location.</li></ul> <div class="mw-heading mw-heading2"><h2 id="Software">Software</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=27" title="Edit section: Software"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/ELKI" title="ELKI">ELKI</a> is an open-source Java data mining toolkit that contains several anomaly detection algorithms, as well as index acceleration for them.</li> <li>PyOD is an open-source Python library developed specifically for anomaly detection.<sup id="cite_ref-51" class="reference"><a href="#cite_note-51"><span class="cite-bracket">[</span>51<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Scikit-learn" title="Scikit-learn">scikit-learn</a> is an open-source Python library that contains some algorithms for unsupervised anomaly detection.</li> <li><a href="/wiki/Wolfram_Mathematica" title="Wolfram Mathematica">Wolfram Mathematica</a> provides functionality for unsupervised anomaly detection across multiple data types <sup id="cite_ref-52" class="reference"><a href="#cite_note-52"><span class="cite-bracket">[</span>52<span class="cite-bracket">]</span></a></sup></li></ul> <div class="mw-heading mw-heading2"><h2 id="Datasets">Datasets</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=28" title="Edit section: Datasets"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a rel="nofollow" class="external text" href="http://www.dbs.ifi.lmu.de/research/outlier-evaluation/">Anomaly detection benchmark data repository</a> with carefully chosen data sets of the <a href="/wiki/Ludwig-Maximilians-Universit%C3%A4t_M%C3%BCnchen" class="mw-redirect" title="Ludwig-Maximilians-Universität München">Ludwig-Maximilians-Universität München</a>; <a rel="nofollow" class="external text" href="http://lapad-web.icmc.usp.br/repositories/outlier-evaluation/">Mirror</a> <a rel="nofollow" class="external text" href="https://web.archive.org/web/20220331072353/http://lapad-web.icmc.usp.br/repositories/outlier-evaluation/">Archived</a> 2022-03-31 at the <a href="/wiki/Wayback_Machine" title="Wayback Machine">Wayback Machine</a> at <a href="/wiki/University_of_S%C3%A3o_Paulo" title="University of São Paulo">University of São Paulo</a>.</li> <li><a rel="nofollow" class="external text" href="http://odds.cs.stonybrook.edu/">ODDS</a> – ODDS: A large collection of publicly available outlier detection datasets with <a href="/wiki/Ground_truth" title="Ground truth">ground truth</a> in different domains.</li> <li><a rel="nofollow" class="external text" href="https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/OPQMVF">Unsupervised Anomaly Detection Benchmark</a> at Harvard Dataverse: Datasets for Unsupervised Anomaly Detection with ground truth.</li> <li><a rel="nofollow" class="external text" href="https://researchdata.edu.au/kmash-repository-outlier-detection/1733742/">KMASH Data Repository</a> at Research Data Australia having more than 12,000 anomaly detection datasets with ground truth.</li></ul> <div class="mw-heading mw-heading2"><h2 id="See_also">See also</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=29" title="Edit section: See also"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Change_detection" title="Change detection">Change detection</a></li> <li><a href="/wiki/Statistical_process_control" title="Statistical process control">Statistical process control</a></li> <li><a href="/wiki/Novelty_detection" title="Novelty detection">Novelty detection</a></li> <li><a href="/wiki/Hierarchical_temporal_memory" title="Hierarchical temporal memory">Hierarchical temporal memory</a></li></ul> <div class="mw-heading mw-heading2"><h2 id="References">References</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Anomaly_detection&action=edit&section=30" title="Edit section: References"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1239543626">.mw-parser-output .reflist{margin-bottom:0.5em;list-style-type:decimal}@media screen{.mw-parser-output .reflist{font-size:90%}}.mw-parser-output .reflist .references{font-size:100%;margin-bottom:0;list-style-type:inherit}.mw-parser-output .reflist-columns-2{column-width:30em}.mw-parser-output .reflist-columns-3{column-width:25em}.mw-parser-output .reflist-columns{margin-top:0.3em}.mw-parser-output .reflist-columns ol{margin-top:0}.mw-parser-output .reflist-columns li{page-break-inside:avoid;break-inside:avoid-column}.mw-parser-output .reflist-upper-alpha{list-style-type:upper-alpha}.mw-parser-output .reflist-upper-roman{list-style-type:upper-roman}.mw-parser-output .reflist-lower-alpha{list-style-type:lower-alpha}.mw-parser-output .reflist-lower-greek{list-style-type:lower-greek}.mw-parser-output .reflist-lower-roman{list-style-type:lower-roman}</style><div class="reflist reflist-columns references-column-width" style="column-width: 30em;"> <ol class="references"> <li id="cite_note-ChandolaSurvey-1"><span class="mw-cite-backlink">^ <a href="#cite_ref-ChandolaSurvey_1-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-ChandolaSurvey_1-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-ChandolaSurvey_1-2"><sup><i><b>c</b></i></sup></a> <a href="#cite_ref-ChandolaSurvey_1-3"><sup><i><b>d</b></i></sup></a></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/6/65/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}</style><cite id="CITEREFChandolaBanerjeeKumar2009" class="citation journal cs1">Chandola, V.; Banerjee, A.; Kumar, V. (2009). "Anomaly detection: A survey". <i><a href="/wiki/ACM_Computing_Surveys" title="ACM Computing Surveys">ACM Computing Surveys</a></i>. <b>41</b> (3): 1–58. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F1541880.1541882">10.1145/1541880.1541882</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:207172599">207172599</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=ACM+Computing+Surveys&rft.atitle=Anomaly+detection%3A+A+survey&rft.volume=41&rft.issue=3&rft.pages=1-58&rft.date=2009&rft_id=info%3Adoi%2F10.1145%2F1541880.1541882&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A207172599%23id-name%3DS2CID&rft.aulast=Chandola&rft.aufirst=V.&rft.au=Banerjee%2C+A.&rft.au=Kumar%2C+V.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Hawkins_1980-2"><span class="mw-cite-backlink">^ <a href="#cite_ref-Hawkins_1980_2-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Hawkins_1980_2-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFHawkins1980" class="citation book cs1">Hawkins, Douglas M. (1980). <i>Identification of Outliers</i>. Springer. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-0-412-21900-9" title="Special:BookSources/978-0-412-21900-9"><bdi>978-0-412-21900-9</bdi></a>. <a href="/wiki/OCLC_(identifier)" class="mw-redirect" title="OCLC (identifier)">OCLC</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/oclc/6912274">6912274</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=book&rft.btitle=Identification+of+Outliers&rft.pub=Springer&rft.date=1980&rft_id=info%3Aoclcnum%2F6912274&rft.isbn=978-0-412-21900-9&rft.aulast=Hawkins&rft.aufirst=Douglas+M.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Outliers_in_statistical_data-3"><span class="mw-cite-backlink">^ <a href="#cite_ref-Outliers_in_statistical_data_3-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Outliers_in_statistical_data_3-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFBarnettLewis1978" class="citation book cs1">Barnett, Vic; Lewis, Lewis (1978). <i>Outliers in statistical data</i>. Wiley. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-0-471-99599-9" title="Special:BookSources/978-0-471-99599-9"><bdi>978-0-471-99599-9</bdi></a>. <a href="/wiki/OCLC_(identifier)" class="mw-redirect" title="OCLC (identifier)">OCLC</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/oclc/1150938591">1150938591</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=book&rft.btitle=Outliers+in+statistical+data&rft.pub=Wiley&rft.date=1978&rft_id=info%3Aoclcnum%2F1150938591&rft.isbn=978-0-471-99599-9&rft.aulast=Barnett&rft.aufirst=Vic&rft.au=Lewis%2C+Lewis&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Kemmerer-2002-4"><span class="mw-cite-backlink">^ <a href="#cite_ref-Kemmerer-2002_4-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Kemmerer-2002_4-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-Kemmerer-2002_4-2"><sup><i><b>c</b></i></sup></a> <a href="#cite_ref-Kemmerer-2002_4-3"><sup><i><b>d</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFKemmererVigna2002" class="citation journal cs1">Kemmerer, R.A.; Vigna, G. (April 2002). <a rel="nofollow" class="external text" href="https://dx.doi.org/10.1109/mc.2002.1012428">"Intrusion detection: a brief history and overview"</a>. <i>Computer</i>. <b>35</b> (4): supl27–supl30. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2Fmc.2002.1012428">10.1109/mc.2002.1012428</a>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/0018-9162">0018-9162</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Computer&rft.atitle=Intrusion+detection%3A+a+brief+history+and+overview&rft.volume=35&rft.issue=4&rft.pages=supl27-supl30&rft.date=2002-04&rft_id=info%3Adoi%2F10.1109%2Fmc.2002.1012428&rft.issn=0018-9162&rft.aulast=Kemmerer&rft.aufirst=R.A.&rft.au=Vigna%2C+G.&rft_id=http%3A%2F%2Fdx.doi.org%2F10.1109%2Fmc.2002.1012428&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-5"><span class="mw-cite-backlink"><b><a href="#cite_ref-5">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFAggarwal2017" class="citation book cs1">Aggarwal, Charu (2017). <i>Outlier Analysis</i>. Springer Publishing Company, Incorporated. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-3319475776" title="Special:BookSources/978-3319475776"><bdi>978-3319475776</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=book&rft.btitle=Outlier+Analysis&rft.pub=Springer+Publishing+Company%2C+Incorporated&rft.date=2017&rft.isbn=978-3319475776&rft.aulast=Aggarwal&rft.aufirst=Charu&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-6"><span class="mw-cite-backlink"><b><a href="#cite_ref-6">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFDenning1987" class="citation journal cs1 cs1-prop-long-vol"><a href="/wiki/Dorothy_E._Denning" title="Dorothy E. Denning">Denning, D. E.</a> (1987). <a rel="nofollow" class="external text" href="http://apps.dtic.mil/dtic/tr/fulltext/u2/a484998.pdf">"An Intrusion-Detection Model"</a> <span class="cs1-format">(PDF)</span>. <i><a href="/wiki/IEEE_Transactions_on_Software_Engineering" title="IEEE Transactions on Software Engineering">IEEE Transactions on Software Engineering</a></i>. SE-13 (2): 222–232. <a href="/wiki/CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.5127">10.1.1.102.5127</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2FTSE.1987.232894">10.1109/TSE.1987.232894</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:10028835">10028835</a>. <a rel="nofollow" class="external text" href="https://web.archive.org/web/20150622044937/http://www.dtic.mil/dtic/tr/fulltext/u2/a484998.pdf">Archived</a> <span class="cs1-format">(PDF)</span> from the original on June 22, 2015.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=IEEE+Transactions+on+Software+Engineering&rft.atitle=An+Intrusion-Detection+Model&rft.volume=SE-13&rft.issue=2&rft.pages=222-232&rft.date=1987&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fsummary%3Fdoi%3D10.1.1.102.5127%23id-name%3DCiteSeerX&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A10028835%23id-name%3DS2CID&rft_id=info%3Adoi%2F10.1109%2FTSE.1987.232894&rft.aulast=Denning&rft.aufirst=D.+E.&rft_id=http%3A%2F%2Fapps.dtic.mil%2Fdtic%2Ftr%2Ffulltext%2Fu2%2Fa484998.pdf&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-7"><span class="mw-cite-backlink"><b><a href="#cite_ref-7">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFTengChenLu1990" class="citation book cs1">Teng, H. S.; Chen, K.; Lu, S. C. (1990). "Adaptive real-time anomaly detection using inductively generated sequential patterns". <a rel="nofollow" class="external text" href="http://www.cs.unc.edu/~jeffay/courses/nidsS05/ai/Teng-AdaptiveRTAnomaly-SnP90.pdf"><i>Proceedings. 1990 IEEE Computer Society Symposium on Research in Security and Privacy</i></a> <span class="cs1-format">(PDF)</span>. pp. 278–284. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2FRISP.1990.63857">10.1109/RISP.1990.63857</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-0-8186-2060-7" title="Special:BookSources/978-0-8186-2060-7"><bdi>978-0-8186-2060-7</bdi></a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:35632142">35632142</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.atitle=Adaptive+real-time+anomaly+detection+using+inductively+generated+sequential+patterns&rft.btitle=Proceedings.+1990+IEEE+Computer+Society+Symposium+on+Research+in+Security+and+Privacy&rft.pages=278-284&rft.date=1990&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A35632142%23id-name%3DS2CID&rft_id=info%3Adoi%2F10.1109%2FRISP.1990.63857&rft.isbn=978-0-8186-2060-7&rft.aulast=Teng&rft.aufirst=H.+S.&rft.au=Chen%2C+K.&rft.au=Lu%2C+S.+C.&rft_id=http%3A%2F%2Fwww.cs.unc.edu%2F~jeffay%2Fcourses%2FnidsS05%2Fai%2FTeng-AdaptiveRTAnomaly-SnP90.pdf&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-8"><span class="mw-cite-backlink"><b><a href="#cite_ref-8">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFJonesSielken2000" class="citation journal cs1">Jones, Anita K.; Sielken, Robert S. (2000). <a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=349277a67468e7f6a5bfc487ab125887c6925229">"Computer System Intrusion Detection: A Survey"</a>. <i>Computer Science Technical Report</i>. Department of Computer Science, University of Virginia: 1–25}.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Computer+Science+Technical+Report&rft.atitle=Computer+System+Intrusion+Detection%3A+A+Survey&rft.pages=1-25%7D&rft.date=2000&rft.aulast=Jones&rft.aufirst=Anita+K.&rft.au=Sielken%2C+Robert+S.&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fdocument%3Frepid%3Drep1%26type%3Dpdf%26doi%3D349277a67468e7f6a5bfc487ab125887c6925229&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-9"><span class="mw-cite-backlink"><b><a href="#cite_ref-9">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFStojanovićBožićHofer-SchmitzNahrgang2021" class="citation journal cs1">Stojanović, Branka; Božić, Josip; Hofer-Schmitz, Katharina; Nahrgang, Kai; Weber, Andreas; Badii, Atta; Sundaram, Maheshkumar; Jordan, Elliot; Runevic, Joel (January 2021). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7956727">"Follow the Trail: Machine Learning for Fraud Detection in Fintech Applications"</a>. <i>Sensors</i>. <b>21</b> (5): 1594. <a href="/wiki/Bibcode_(identifier)" class="mw-redirect" title="Bibcode (identifier)">Bibcode</a>:<a rel="nofollow" class="external text" href="https://ui.adsabs.harvard.edu/abs/2021Senso..21.1594S">2021Senso..21.1594S</a>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.3390%2Fs21051594">10.3390/s21051594</a></span>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1424-8220">1424-8220</a>. <a href="/wiki/PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7956727">7956727</a></span>. <a href="/wiki/PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/33668773">33668773</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Sensors&rft.atitle=Follow+the+Trail%3A+Machine+Learning+for+Fraud+Detection+in+Fintech+Applications&rft.volume=21&rft.issue=5&rft.pages=1594&rft.date=2021-01&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC7956727%23id-name%3DPMC&rft_id=info%3Abibcode%2F2021Senso..21.1594S&rft_id=info%3Apmid%2F33668773&rft_id=info%3Adoi%2F10.3390%2Fs21051594&rft.issn=1424-8220&rft.aulast=Stojanovi%C4%87&rft.aufirst=Branka&rft.au=Bo%C5%BEi%C4%87%2C+Josip&rft.au=Hofer-Schmitz%2C+Katharina&rft.au=Nahrgang%2C+Kai&rft.au=Weber%2C+Andreas&rft.au=Badii%2C+Atta&rft.au=Sundaram%2C+Maheshkumar&rft.au=Jordan%2C+Elliot&rft.au=Runevic%2C+Joel&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC7956727&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-10"><span class="mw-cite-backlink"><b><a href="#cite_ref-10">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFAhmedMahmoodIslam2016" class="citation journal cs1">Ahmed, Mohiuddin; Mahmood, Abdun Naser; Islam, Md. Rafiqul (February 2016). <a rel="nofollow" class="external text" href="https://dx.doi.org/10.1016/j.future.2015.01.001">"A survey of anomaly detection techniques in financial domain"</a>. <i>Future Generation Computer Systems</i>. <b>55</b>: 278–288. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1016%2Fj.future.2015.01.001">10.1016/j.future.2015.01.001</a>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/0167-739X">0167-739X</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:204982937">204982937</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Future+Generation+Computer+Systems&rft.atitle=A+survey+of+anomaly+detection+techniques+in+financial+domain&rft.volume=55&rft.pages=278-288&rft.date=2016-02&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A204982937%23id-name%3DS2CID&rft.issn=0167-739X&rft_id=info%3Adoi%2F10.1016%2Fj.future.2015.01.001&rft.aulast=Ahmed&rft.aufirst=Mohiuddin&rft.au=Mahmood%2C+Abdun+Naser&rft.au=Islam%2C+Md.+Rafiqul&rft_id=http%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.future.2015.01.001&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-11"><span class="mw-cite-backlink"><b><a href="#cite_ref-11">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFTomek1976" class="citation journal cs1">Tomek, Ivan (1976). "An Experiment with the Edited Nearest-Neighbor Rule". <i><a href="/wiki/IEEE_Systems,_Man,_and_Cybernetics_Society" title="IEEE Systems, Man, and Cybernetics Society">IEEE Transactions on Systems, Man, and Cybernetics</a></i>. <b>6</b> (6): 448–452. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2FTSMC.1976.4309523">10.1109/TSMC.1976.4309523</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=IEEE+Transactions+on+Systems%2C+Man%2C+and+Cybernetics&rft.atitle=An+Experiment+with+the+Edited+Nearest-Neighbor+Rule&rft.volume=6&rft.issue=6&rft.pages=448-452&rft.date=1976&rft_id=info%3Adoi%2F10.1109%2FTSMC.1976.4309523&rft.aulast=Tomek&rft.aufirst=Ivan&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-12"><span class="mw-cite-backlink"><b><a href="#cite_ref-12">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFSmithMartinez2011" class="citation book cs1">Smith, M. R.; Martinez, T. (2011). <a rel="nofollow" class="external text" href="http://axon.cs.byu.edu/papers/smith.ijcnn2011.pdf">"Improving classification accuracy by identifying and removing instances that should be misclassified"</a> <span class="cs1-format">(PDF)</span>. <i>The 2011 International Joint Conference on Neural Networks</i>. p. 2690. <a href="/wiki/CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.1371">10.1.1.221.1371</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2FIJCNN.2011.6033571">10.1109/IJCNN.2011.6033571</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-4244-9635-8" title="Special:BookSources/978-1-4244-9635-8"><bdi>978-1-4244-9635-8</bdi></a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:5809822">5809822</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.atitle=Improving+classification+accuracy+by+identifying+and+removing+instances+that+should+be+misclassified&rft.btitle=The+2011+International+Joint+Conference+on+Neural+Networks&rft.pages=2690&rft.date=2011&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fsummary%3Fdoi%3D10.1.1.221.1371%23id-name%3DCiteSeerX&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A5809822%23id-name%3DS2CID&rft_id=info%3Adoi%2F10.1109%2FIJCNN.2011.6033571&rft.isbn=978-1-4244-9635-8&rft.aulast=Smith&rft.aufirst=M.+R.&rft.au=Martinez%2C+T.&rft_id=http%3A%2F%2Faxon.cs.byu.edu%2Fpapers%2Fsmith.ijcnn2011.pdf&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Qasim-2023-13"><span class="mw-cite-backlink">^ <a href="#cite_ref-Qasim-2023_13-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Qasim-2023_13-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-Qasim-2023_13-2"><sup><i><b>c</b></i></sup></a> <a href="#cite_ref-Qasim-2023_13-3"><sup><i><b>d</b></i></sup></a> <a href="#cite_ref-Qasim-2023_13-4"><sup><i><b>e</b></i></sup></a> <a href="#cite_ref-Qasim-2023_13-5"><sup><i><b>f</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFQasimVerdu2023" class="citation journal cs1">Qasim, Maryam; Verdu, Elena (2023-06-01). <a rel="nofollow" class="external text" href="https://doi.org/10.1016%2Fj.rineng.2023.101026">"Video anomaly detection system using deep convolutional and recurrent models"</a>. <i>Results in Engineering</i>. <b>18</b>: 101026. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.1016%2Fj.rineng.2023.101026">10.1016/j.rineng.2023.101026</a></span>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/2590-1230">2590-1230</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:257728239">257728239</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Results+in+Engineering&rft.atitle=Video+anomaly+detection+system+using+deep+convolutional+and+recurrent+models&rft.volume=18&rft.pages=101026&rft.date=2023-06-01&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A257728239%23id-name%3DS2CID&rft.issn=2590-1230&rft_id=info%3Adoi%2F10.1016%2Fj.rineng.2023.101026&rft.aulast=Qasim&rft.aufirst=Maryam&rft.au=Verdu%2C+Elena&rft_id=https%3A%2F%2Fdoi.org%2F10.1016%252Fj.rineng.2023.101026&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-14"><span class="mw-cite-backlink"><b><a href="#cite_ref-14">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFZhangChowdheryBahlJamieson2015" class="citation book cs1">Zhang, Tan; Chowdhery, Aakanksha; Bahl, Paramvir (Victor); Jamieson, Kyle; Banerjee, Suman (2015-09-07). <a rel="nofollow" class="external text" href="https://doi.org/10.1145/2789168.2790123">"The Design and Implementation of a Wireless Video Surveillance System"</a>. <a rel="nofollow" class="external text" href="https://discovery.ucl.ac.uk/id/eprint/1506446/"><i>Proceedings of the 21st Annual International Conference on Mobile Computing and Networking</i></a>. MobiCom '15. New York, NY, USA: Association for Computing Machinery. pp. 426–438. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F2789168.2790123">10.1145/2789168.2790123</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-4503-3619-2" title="Special:BookSources/978-1-4503-3619-2"><bdi>978-1-4503-3619-2</bdi></a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:12310150">12310150</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.atitle=The+Design+and+Implementation+of+a+Wireless+Video+Surveillance+System&rft.btitle=Proceedings+of+the+21st+Annual+International+Conference+on+Mobile+Computing+and+Networking&rft.place=New+York%2C+NY%2C+USA&rft.series=MobiCom+%2715&rft.pages=426-438&rft.pub=Association+for+Computing+Machinery&rft.date=2015-09-07&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A12310150%23id-name%3DS2CID&rft_id=info%3Adoi%2F10.1145%2F2789168.2790123&rft.isbn=978-1-4503-3619-2&rft.aulast=Zhang&rft.aufirst=Tan&rft.au=Chowdhery%2C+Aakanksha&rft.au=Bahl%2C+Paramvir+%28Victor%29&rft.au=Jamieson%2C+Kyle&rft.au=Banerjee%2C+Suman&rft_id=https%3A%2F%2Fdoi.org%2F10.1145%2F2789168.2790123&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Gow-2018-15"><span class="mw-cite-backlink">^ <a href="#cite_ref-Gow-2018_15-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Gow-2018_15-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-Gow-2018_15-2"><sup><i><b>c</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFGowRabhiVenugopal2018" class="citation journal cs1">Gow, Richard; Rabhi, Fethi A.; Venugopal, Srikumar (2018). <a rel="nofollow" class="external text" href="https://ieeexplore.ieee.org/document/8101009">"Anomaly Detection in Complex Real World Application Systems"</a>. <i>IEEE Transactions on Network and Service Management</i>. <b>15</b>: 83–96. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2FTNSM.2017.2771403">10.1109/TNSM.2017.2771403</a>. <a href="/wiki/Hdl_(identifier)" class="mw-redirect" title="Hdl (identifier)">hdl</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://hdl.handle.net/1959.4%2Funsworks_73660">1959.4/unsworks_73660</a></span>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:3883483">3883483</a><span class="reference-accessdate">. Retrieved <span class="nowrap">2023-11-08</span></span>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=IEEE+Transactions+on+Network+and+Service+Management&rft.atitle=Anomaly+Detection+in+Complex+Real+World+Application+Systems&rft.volume=15&rft.pages=83-96&rft.date=2018&rft_id=info%3Ahdl%2F1959.4%2Funsworks_73660&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A3883483%23id-name%3DS2CID&rft_id=info%3Adoi%2F10.1109%2FTNSM.2017.2771403&rft.aulast=Gow&rft.aufirst=Richard&rft.au=Rabhi%2C+Fethi+A.&rft.au=Venugopal%2C+Srikumar&rft_id=https%3A%2F%2Fieeexplore.ieee.org%2Fdocument%2F8101009&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Chatterjee-2022-16"><span class="mw-cite-backlink">^ <a href="#cite_ref-Chatterjee-2022_16-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Chatterjee-2022_16-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFChatterjeeAhmed2022" class="citation journal cs1">Chatterjee, Ayan; Ahmed, Bestoun S. (August 2022). <a rel="nofollow" class="external text" href="https://doi.org/10.1016%2Fj.iot.2022.100568">"IoT anomaly detection methods and applications: A survey"</a>. <i>Internet of Things</i>. <b>19</b>: 100568. <a href="/wiki/ArXiv_(identifier)" class="mw-redirect" title="ArXiv (identifier)">arXiv</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://arxiv.org/abs/2207.09092">2207.09092</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.1016%2Fj.iot.2022.100568">10.1016/j.iot.2022.100568</a></span>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/2542-6605">2542-6605</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:250644468">250644468</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Internet+of+Things&rft.atitle=IoT+anomaly+detection+methods+and+applications%3A+A+survey&rft.volume=19&rft.pages=100568&rft.date=2022-08&rft_id=info%3Aarxiv%2F2207.09092&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A250644468%23id-name%3DS2CID&rft.issn=2542-6605&rft_id=info%3Adoi%2F10.1016%2Fj.iot.2022.100568&rft.aulast=Chatterjee&rft.aufirst=Ayan&rft.au=Ahmed%2C+Bestoun+S.&rft_id=https%3A%2F%2Fdoi.org%2F10.1016%252Fj.iot.2022.100568&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Garg-2020-17"><span class="mw-cite-backlink">^ <a href="#cite_ref-Garg-2020_17-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Garg-2020_17-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFGargKaurBatraKaddoum2020" class="citation journal cs1">Garg, Sahil; Kaur, Kuljeet; Batra, Shalini; Kaddoum, Georges; Kumar, Neeraj; Boukerche, Azzedine (2020-03-01). <a rel="nofollow" class="external text" href="https://www.sciencedirect.com/science/article/pii/S0167739X19319703">"A multi-stage anomaly detection scheme for augmenting the security in IoT-enabled applications"</a>. <i>Future Generation Computer Systems</i>. <b>104</b>: 105–118. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1016%2Fj.future.2019.09.038">10.1016/j.future.2019.09.038</a>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/0167-739X">0167-739X</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:204077191">204077191</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Future+Generation+Computer+Systems&rft.atitle=A+multi-stage+anomaly+detection+scheme+for+augmenting+the+security+in+IoT-enabled+applications&rft.volume=104&rft.pages=105-118&rft.date=2020-03-01&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A204077191%23id-name%3DS2CID&rft.issn=0167-739X&rft_id=info%3Adoi%2F10.1016%2Fj.future.2019.09.038&rft.aulast=Garg&rft.aufirst=Sahil&rft.au=Kaur%2C+Kuljeet&rft.au=Batra%2C+Shalini&rft.au=Kaddoum%2C+Georges&rft.au=Kumar%2C+Neeraj&rft.au=Boukerche%2C+Azzedine&rft_id=https%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0167739X19319703&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Martí-2015-18"><span class="mw-cite-backlink">^ <a href="#cite_ref-Martí-2015_18-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Martí-2015_18-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-Martí-2015_18-2"><sup><i><b>c</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFMartíSanchez-PiMolinaGarcia2015" class="citation journal cs1">Martí, Luis; Sanchez-Pi, Nayat; Molina, José Manuel; Garcia, Ana Cristina Bicharra (February 2015). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367333">"Anomaly Detection Based on Sensor Data in Petroleum Industry Applications"</a>. <i>Sensors</i>. <b>15</b> (2): 2774–2797. <a href="/wiki/Bibcode_(identifier)" class="mw-redirect" title="Bibcode (identifier)">Bibcode</a>:<a rel="nofollow" class="external text" href="https://ui.adsabs.harvard.edu/abs/2015Senso..15.2774M">2015Senso..15.2774M</a>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.3390%2Fs150202774">10.3390/s150202774</a></span>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1424-8220">1424-8220</a>. <a href="/wiki/PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367333">4367333</a></span>. <a href="/wiki/PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/25633599">25633599</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Sensors&rft.atitle=Anomaly+Detection+Based+on+Sensor+Data+in+Petroleum+Industry+Applications&rft.volume=15&rft.issue=2&rft.pages=2774-2797&rft.date=2015-02&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC4367333%23id-name%3DPMC&rft_id=info%3Abibcode%2F2015Senso..15.2774M&rft_id=info%3Apmid%2F25633599&rft_id=info%3Adoi%2F10.3390%2Fs150202774&rft.issn=1424-8220&rft.aulast=Mart%C3%AD&rft.aufirst=Luis&rft.au=Sanchez-Pi%2C+Nayat&rft.au=Molina%2C+Jos%C3%A9+Manuel&rft.au=Garcia%2C+Ana+Cristina+Bicharra&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC4367333&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Aljameel-2022-19"><span class="mw-cite-backlink">^ <a href="#cite_ref-Aljameel-2022_19-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Aljameel-2022_19-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFAljameelAlomariAlismailKhawaher2022" class="citation journal cs1">Aljameel, Sumayh S.; Alomari, Dorieh M.; Alismail, Shatha; Khawaher, Fatimah; Alkhudhair, Aljawharah A.; Aljubran, Fatimah; Alzannan, Razan M. (August 2022). <a rel="nofollow" class="external text" href="https://doi.org/10.3390%2Fcomputation10080138">"An Anomaly Detection Model for Oil and Gas Pipelines Using Machine Learning"</a>. <i>Computation</i>. <b>10</b> (8): 138. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.3390%2Fcomputation10080138">10.3390/computation10080138</a></span>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/2079-3197">2079-3197</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Computation&rft.atitle=An+Anomaly+Detection+Model+for+Oil+and+Gas+Pipelines+Using+Machine+Learning&rft.volume=10&rft.issue=8&rft.pages=138&rft.date=2022-08&rft_id=info%3Adoi%2F10.3390%2Fcomputation10080138&rft.issn=2079-3197&rft.aulast=Aljameel&rft.aufirst=Sumayh+S.&rft.au=Alomari%2C+Dorieh+M.&rft.au=Alismail%2C+Shatha&rft.au=Khawaher%2C+Fatimah&rft.au=Alkhudhair%2C+Aljawharah+A.&rft.au=Aljubran%2C+Fatimah&rft.au=Alzannan%2C+Razan+M.&rft_id=https%3A%2F%2Fdoi.org%2F10.3390%252Fcomputation10080138&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-ZimekFilzmoser2018-20"><span class="mw-cite-backlink"><b><a href="#cite_ref-ZimekFilzmoser2018_20-0">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFZimekFilzmoser2018" class="citation journal cs1"><a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, Arthur</a>; Filzmoser, Peter (2018). <a rel="nofollow" class="external text" href="https://web.archive.org/web/20211114121638/https://findresearcher.sdu.dk:8443/ws/files/153197807/There_and_Back_Again.pdf">"There and back again: Outlier detection between statistical reasoning and data mining algorithms"</a> <span class="cs1-format">(PDF)</span>. <i>Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery</i>. <b>8</b> (6): e1280. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1002%2Fwidm.1280">10.1002/widm.1280</a>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1942-4787">1942-4787</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:53305944">53305944</a>. Archived from <a rel="nofollow" class="external text" href="https://findresearcher.sdu.dk:8443/ws/files/153197807/There_and_Back_Again.pdf">the original</a> <span class="cs1-format">(PDF)</span> on 2021-11-14<span class="reference-accessdate">. Retrieved <span class="nowrap">2019-12-09</span></span>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Wiley+Interdisciplinary+Reviews%3A+Data+Mining+and+Knowledge+Discovery&rft.atitle=There+and+back+again%3A+Outlier+detection+between+statistical+reasoning+and+data+mining+algorithms&rft.volume=8&rft.issue=6&rft.pages=e1280&rft.date=2018&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A53305944%23id-name%3DS2CID&rft.issn=1942-4787&rft_id=info%3Adoi%2F10.1002%2Fwidm.1280&rft.aulast=Zimek&rft.aufirst=Arthur&rft.au=Filzmoser%2C+Peter&rft_id=https%3A%2F%2Ffindresearcher.sdu.dk%3A8443%2Fws%2Ffiles%2F153197807%2FThere_and_Back_Again.pdf&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-CamposZimek2016-21"><span class="mw-cite-backlink"><b><a href="#cite_ref-CamposZimek2016_21-0">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFCamposZimekSanderCampello2016" class="citation journal cs1">Campos, Guilherme O.; <a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, Arthur</a>; Sander, Jörg; Campello, Ricardo J. G. B.; Micenková, Barbora; Schubert, Erich; Assent, Ira; Houle, Michael E. (2016). "On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study". <i>Data Mining and Knowledge Discovery</i>. <b>30</b> (4): 891. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2Fs10618-015-0444-8">10.1007/s10618-015-0444-8</a>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1384-5810">1384-5810</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:1952214">1952214</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Data+Mining+and+Knowledge+Discovery&rft.atitle=On+the+evaluation+of+unsupervised+outlier+detection%3A+measures%2C+datasets%2C+and+an+empirical+study&rft.volume=30&rft.issue=4&rft.pages=891&rft.date=2016&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A1952214%23id-name%3DS2CID&rft.issn=1384-5810&rft_id=info%3Adoi%2F10.1007%2Fs10618-015-0444-8&rft.aulast=Campos&rft.aufirst=Guilherme+O.&rft.au=Zimek%2C+Arthur&rft.au=Sander%2C+J%C3%B6rg&rft.au=Campello%2C+Ricardo+J.+G.+B.&rft.au=Micenkov%C3%A1%2C+Barbora&rft.au=Schubert%2C+Erich&rft.au=Assent%2C+Ira&rft.au=Houle%2C+Michael+E.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-22"><span class="mw-cite-backlink"><b><a href="#cite_ref-22">^</a></b></span> <span class="reference-text"><a rel="nofollow" class="external text" href="http://www.dbs.ifi.lmu.de/research/outlier-evaluation/">Anomaly detection benchmark data repository</a> of the <a href="/wiki/Ludwig-Maximilians-Universit%C3%A4t_M%C3%BCnchen" class="mw-redirect" title="Ludwig-Maximilians-Universität München">Ludwig-Maximilians-Universität München</a>; <a rel="nofollow" class="external text" href="http://lapad-web.icmc.usp.br/repositories/outlier-evaluation/">Mirror</a> <a rel="nofollow" class="external text" href="https://web.archive.org/web/20220331072353/http://lapad-web.icmc.usp.br/repositories/outlier-evaluation/">Archived</a> 2022-03-31 at the <a href="/wiki/Wayback_Machine" title="Wayback Machine">Wayback Machine</a> at <a href="/wiki/University_of_S%C3%A3o_Paulo" title="University of São Paulo">University of São Paulo</a>.</span> </li> <li id="cite_note-23"><span class="mw-cite-backlink"><b><a href="#cite_ref-23">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFKnorrNgTucakov2000" class="citation journal cs1">Knorr, E. M.; Ng, R. T.; Tucakov, V. (2000). "Distance-based outliers: Algorithms and applications". <i>The VLDB Journal the International Journal on Very Large Data Bases</i>. <b>8</b> (3–4): 237–253. <a href="/wiki/CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.1842">10.1.1.43.1842</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2Fs007780050006">10.1007/s007780050006</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:11707259">11707259</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=The+VLDB+Journal+the+International+Journal+on+Very+Large+Data+Bases&rft.atitle=Distance-based+outliers%3A+Algorithms+and+applications&rft.volume=8&rft.issue=3%E2%80%934&rft.pages=237-253&rft.date=2000&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fsummary%3Fdoi%3D10.1.1.43.1842%23id-name%3DCiteSeerX&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A11707259%23id-name%3DS2CID&rft_id=info%3Adoi%2F10.1007%2Fs007780050006&rft.aulast=Knorr&rft.aufirst=E.+M.&rft.au=Ng%2C+R.+T.&rft.au=Tucakov%2C+V.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-24"><span class="mw-cite-backlink"><b><a href="#cite_ref-24">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFRamaswamyRastogiShim2000" class="citation conference cs1">Ramaswamy, S.; Rastogi, R.; Shim, K. (2000). <i>Efficient algorithms for mining outliers from large data sets</i>. Proceedings of the 2000 ACM SIGMOD international conference on Management of data – SIGMOD '00. p. 427. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F342009.335437">10.1145/342009.335437</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/1-58113-217-4" title="Special:BookSources/1-58113-217-4"><bdi>1-58113-217-4</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=conference&rft.btitle=Efficient+algorithms+for+mining+outliers+from+large+data+sets&rft.pages=427&rft.date=2000&rft_id=info%3Adoi%2F10.1145%2F342009.335437&rft.isbn=1-58113-217-4&rft.aulast=Ramaswamy&rft.aufirst=S.&rft.au=Rastogi%2C+R.&rft.au=Shim%2C+K.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-25"><span class="mw-cite-backlink"><b><a href="#cite_ref-25">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFAngiulliPizzuti2002" class="citation conference cs1">Angiulli, F.; Pizzuti, C. (2002). <i>Fast Outlier Detection in High Dimensional Spaces</i>. Principles of Data Mining and Knowledge Discovery. Lecture Notes in Computer Science. Vol. 2431. p. 15. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.1007%2F3-540-45681-3_2">10.1007/3-540-45681-3_2</a></span>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-3-540-44037-6" title="Special:BookSources/978-3-540-44037-6"><bdi>978-3-540-44037-6</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=conference&rft.btitle=Fast+Outlier+Detection+in+High+Dimensional+Spaces&rft.series=Lecture+Notes+in+Computer+Science&rft.pages=15&rft.date=2002&rft_id=info%3Adoi%2F10.1007%2F3-540-45681-3_2&rft.isbn=978-3-540-44037-6&rft.aulast=Angiulli&rft.aufirst=F.&rft.au=Pizzuti%2C+C.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-26"><span class="mw-cite-backlink"><b><a href="#cite_ref-26">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFBreunigKriegelNgSander2000" class="citation conference cs1">Breunig, M. M.; <a href="/wiki/Hans-Peter_Kriegel" title="Hans-Peter Kriegel">Kriegel, H.-P.</a>; Ng, R. T.; Sander, J. (2000). <a rel="nofollow" class="external text" href="http://www.dbs.ifi.lmu.de/Publikationen/Papers/LOF.pdf"><i>LOF: Identifying Density-based Local Outliers</i></a> <span class="cs1-format">(PDF)</span>. <i>Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data</i>. <a href="/wiki/SIGMOD" title="SIGMOD">SIGMOD</a>. pp. 93–104. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F335191.335388">10.1145/335191.335388</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/1-58113-217-4" title="Special:BookSources/1-58113-217-4"><bdi>1-58113-217-4</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=conference&rft.jtitle=Proceedings+of+the+2000+ACM+SIGMOD+International+Conference+on+Management+of+Data&rft.atitle=LOF%3A+Identifying+Density-based+Local+Outliers&rft.pages=93-104&rft.date=2000&rft_id=info%3Adoi%2F10.1145%2F335191.335388&rft.isbn=1-58113-217-4&rft.aulast=Breunig&rft.aufirst=M.+M.&rft.au=Kriegel%2C+H.-P.&rft.au=Ng%2C+R.+T.&rft.au=Sander%2C+J.&rft_id=http%3A%2F%2Fwww.dbs.ifi.lmu.de%2FPublikationen%2FPapers%2FLOF.pdf&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-27"><span class="mw-cite-backlink"><b><a href="#cite_ref-27">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFLiuTingZhou2008" class="citation book cs1">Liu, Fei Tony; Ting, Kai Ming; Zhou, Zhi-Hua (December 2008). "Isolation Forest". <a rel="nofollow" class="external text" href="https://www.computer.org/csdl/proceedings/icdm/2008/3502/00/3502a413-abs.html"><i>2008 Eighth IEEE International Conference on Data Mining</i></a>. pp. 413–422. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2FICDM.2008.17">10.1109/ICDM.2008.17</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/9780769535029" title="Special:BookSources/9780769535029"><bdi>9780769535029</bdi></a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:6505449">6505449</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.atitle=Isolation+Forest&rft.btitle=2008+Eighth+IEEE+International+Conference+on+Data+Mining&rft.pages=413-422&rft.date=2008-12&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A6505449%23id-name%3DS2CID&rft_id=info%3Adoi%2F10.1109%2FICDM.2008.17&rft.isbn=9780769535029&rft.aulast=Liu&rft.aufirst=Fei+Tony&rft.au=Ting%2C+Kai+Ming&rft.au=Zhou%2C+Zhi-Hua&rft_id=https%3A%2F%2Fwww.computer.org%2Fcsdl%2Fproceedings%2Ficdm%2F2008%2F3502%2F00%2F3502a413-abs.html&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-28"><span class="mw-cite-backlink"><b><a href="#cite_ref-28">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFLiuTingZhou2012" class="citation journal cs1">Liu, Fei Tony; Ting, Kai Ming; Zhou, Zhi-Hua (March 2012). <a rel="nofollow" class="external text" href="https://www.researchgate.net/publication/239761771">"Isolation-Based Anomaly Detection"</a>. <i>ACM Transactions on Knowledge Discovery from Data</i>. <b>6</b> (1): 1–39. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F2133360.2133363">10.1145/2133360.2133363</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:207193045">207193045</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=ACM+Transactions+on+Knowledge+Discovery+from+Data&rft.atitle=Isolation-Based+Anomaly+Detection&rft.volume=6&rft.issue=1&rft.pages=1-39&rft.date=2012-03&rft_id=info%3Adoi%2F10.1145%2F2133360.2133363&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A207193045%23id-name%3DS2CID&rft.aulast=Liu&rft.aufirst=Fei+Tony&rft.au=Ting%2C+Kai+Ming&rft.au=Zhou%2C+Zhi-Hua&rft_id=https%3A%2F%2Fwww.researchgate.net%2Fpublication%2F239761771&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-29"><span class="mw-cite-backlink"><b><a href="#cite_ref-29">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFSchubertZimekKriegel2012" class="citation journal cs1">Schubert, E.; <a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, A.</a>; <a href="/wiki/Hans-Peter_Kriegel" title="Hans-Peter Kriegel">Kriegel, H. -P.</a> (2012). "Local outlier detection reconsidered: A generalized view on locality with applications to spatial, video, and network outlier detection". <i>Data Mining and Knowledge Discovery</i>. <b>28</b>: 190–237. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2Fs10618-012-0300-z">10.1007/s10618-012-0300-z</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:19036098">19036098</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Data+Mining+and+Knowledge+Discovery&rft.atitle=Local+outlier+detection+reconsidered%3A+A+generalized+view+on+locality+with+applications+to+spatial%2C+video%2C+and+network+outlier+detection&rft.volume=28&rft.pages=190-237&rft.date=2012&rft_id=info%3Adoi%2F10.1007%2Fs10618-012-0300-z&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A19036098%23id-name%3DS2CID&rft.aulast=Schubert&rft.aufirst=E.&rft.au=Zimek%2C+A.&rft.au=Kriegel%2C+H.+-P.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Kriegel-2009-30"><span class="mw-cite-backlink">^ <a href="#cite_ref-Kriegel-2009_30-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Kriegel-2009_30-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFKriegelKrögerSchubertZimek2009" class="citation conference cs1"><a href="/wiki/Hans-Peter_Kriegel" title="Hans-Peter Kriegel">Kriegel, H. P.</a>; Kröger, P.; Schubert, E.; <a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, A.</a> (2009). <i>Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data</i>. Advances in Knowledge Discovery and Data Mining. Lecture Notes in Computer Science. Vol. 5476. p. 831. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2F978-3-642-01307-2_86">10.1007/978-3-642-01307-2_86</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-3-642-01306-5" title="Special:BookSources/978-3-642-01306-5"><bdi>978-3-642-01306-5</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=conference&rft.btitle=Outlier+Detection+in+Axis-Parallel+Subspaces+of+High+Dimensional+Data&rft.series=Lecture+Notes+in+Computer+Science&rft.pages=831&rft.date=2009&rft_id=info%3Adoi%2F10.1007%2F978-3-642-01307-2_86&rft.isbn=978-3-642-01306-5&rft.aulast=Kriegel&rft.aufirst=H.+P.&rft.au=Kr%C3%B6ger%2C+P.&rft.au=Schubert%2C+E.&rft.au=Zimek%2C+A.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-Kriegel-2012-31"><span class="mw-cite-backlink">^ <a href="#cite_ref-Kriegel-2012_31-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-Kriegel-2012_31-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFKriegelKrogerSchubertZimek2012" class="citation conference cs1"><a href="/wiki/Hans-Peter_Kriegel" title="Hans-Peter Kriegel">Kriegel, H. P.</a>; Kroger, P.; Schubert, E.; <a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, A.</a> (2012). <i>Outlier Detection in Arbitrarily Oriented Subspaces</i>. 2012 IEEE 12th International Conference on Data Mining. p. 379. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2FICDM.2012.21">10.1109/ICDM.2012.21</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-4673-4649-8" title="Special:BookSources/978-1-4673-4649-8"><bdi>978-1-4673-4649-8</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=conference&rft.btitle=Outlier+Detection+in+Arbitrarily+Oriented+Subspaces&rft.pages=379&rft.date=2012&rft_id=info%3Adoi%2F10.1109%2FICDM.2012.21&rft.isbn=978-1-4673-4649-8&rft.aulast=Kriegel&rft.aufirst=H.+P.&rft.au=Kroger%2C+P.&rft.au=Schubert%2C+E.&rft.au=Zimek%2C+A.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-32"><span class="mw-cite-backlink"><b><a href="#cite_ref-32">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFFanaee-TGama2016" class="citation journal cs1">Fanaee-T, H.; Gama, J. (2016). <a rel="nofollow" class="external text" href="http://repositorio.inesctec.pt/handle/123456789/5381">"Tensor-based anomaly detection: An interdisciplinary survey"</a>. <i>Knowledge-Based Systems</i>. <b>98</b>: 130–147. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1016%2Fj.knosys.2016.01.027">10.1016/j.knosys.2016.01.027</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:16368060">16368060</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Knowledge-Based+Systems&rft.atitle=Tensor-based+anomaly+detection%3A+An+interdisciplinary+survey&rft.volume=98&rft.pages=130-147&rft.date=2016&rft_id=info%3Adoi%2F10.1016%2Fj.knosys.2016.01.027&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A16368060%23id-name%3DS2CID&rft.aulast=Fanaee-T&rft.aufirst=H.&rft.au=Gama%2C+J.&rft_id=http%3A%2F%2Frepositorio.inesctec.pt%2Fhandle%2F123456789%2F5381&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-33"><span class="mw-cite-backlink"><b><a href="#cite_ref-33">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFZimekSchubertKriegel2012" class="citation journal cs1"><a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, A.</a>; Schubert, E.; <a href="/wiki/Hans-Peter_Kriegel" title="Hans-Peter Kriegel">Kriegel, H.-P.</a> (2012). "A survey on unsupervised outlier detection in high-dimensional numerical data". <i>Statistical Analysis and Data Mining</i>. <b>5</b> (5): 363–387. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1002%2Fsam.11161">10.1002/sam.11161</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:6724536">6724536</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Statistical+Analysis+and+Data+Mining&rft.atitle=A+survey+on+unsupervised+outlier+detection+in+high-dimensional+numerical+data&rft.volume=5&rft.issue=5&rft.pages=363-387&rft.date=2012&rft_id=info%3Adoi%2F10.1002%2Fsam.11161&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A6724536%23id-name%3DS2CID&rft.aulast=Zimek&rft.aufirst=A.&rft.au=Schubert%2C+E.&rft.au=Kriegel%2C+H.-P.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-34"><span class="mw-cite-backlink"><b><a href="#cite_ref-34">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFSchölkopfPlattShawe-TaylorSmola2001" class="citation journal cs1"><a href="/wiki/Bernhard_Sch%C3%B6lkopf" title="Bernhard Schölkopf">Schölkopf, B.</a>; Platt, J. C.; Shawe-Taylor, J.; Smola, A. J.; Williamson, R. C. (2001). "Estimating the Support of a High-Dimensional Distribution". <i>Neural Computation</i>. <b>13</b> (7): 1443–71. <a href="/wiki/CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.4.4106">10.1.1.4.4106</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1162%2F089976601750264965">10.1162/089976601750264965</a>. <a href="/wiki/PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/11440593">11440593</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:2110475">2110475</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Neural+Computation&rft.atitle=Estimating+the+Support+of+a+High-Dimensional+Distribution&rft.volume=13&rft.issue=7&rft.pages=1443-71&rft.date=2001&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fsummary%3Fdoi%3D10.1.1.4.4106%23id-name%3DCiteSeerX&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A2110475%23id-name%3DS2CID&rft_id=info%3Apmid%2F11440593&rft_id=info%3Adoi%2F10.1162%2F089976601750264965&rft.aulast=Sch%C3%B6lkopf&rft.aufirst=B.&rft.au=Platt%2C+J.+C.&rft.au=Shawe-Taylor%2C+J.&rft.au=Smola%2C+A.+J.&rft.au=Williamson%2C+R.+C.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-replicator-35"><span class="mw-cite-backlink">^ <a href="#cite_ref-replicator_35-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-replicator_35-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-replicator_35-2"><sup><i><b>c</b></i></sup></a></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFHawkinsHeWilliamsBaxter2002" class="citation book cs1">Hawkins, Simon; He, Hongxing; Williams, Graham; Baxter, Rohan (2002). "Outlier Detection Using Replicator Neural Networks". <i>Data Warehousing and Knowledge Discovery</i>. Lecture Notes in Computer Science. Vol. 2454. pp. 170–180. <a href="/wiki/CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.3366">10.1.1.12.3366</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2F3-540-46145-0_17">10.1007/3-540-46145-0_17</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-3-540-44123-6" title="Special:BookSources/978-3-540-44123-6"><bdi>978-3-540-44123-6</bdi></a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:6436930">6436930</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.atitle=Outlier+Detection+Using+Replicator+Neural+Networks&rft.btitle=Data+Warehousing+and+Knowledge+Discovery&rft.series=Lecture+Notes+in+Computer+Science&rft.pages=170-180&rft.date=2002&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fsummary%3Fdoi%3D10.1.1.12.3366%23id-name%3DCiteSeerX&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A6436930%23id-name%3DS2CID&rft_id=info%3Adoi%2F10.1007%2F3-540-46145-0_17&rft.isbn=978-3-540-44123-6&rft.aulast=Hawkins&rft.aufirst=Simon&rft.au=He%2C+Hongxing&rft.au=Williams%2C+Graham&rft.au=Baxter%2C+Rohan&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-36"><span class="mw-cite-backlink"><b><a href="#cite_ref-36">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFAnCho2015" class="citation journal cs1">An, J.; Cho, S. (2015). <a rel="nofollow" class="external text" href="http://dm.snu.ac.kr/static/docs/TR/SNUDM-TR-2015-03.pdf">"Variational autoencoder based anomaly detection using reconstruction probability"</a> <span class="cs1-format">(PDF)</span>. <i>Special Lecture on IE</i>. <b>2</b> (1): 1–18. SNUDM-TR-2015-03.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Special+Lecture+on+IE&rft.atitle=Variational+autoencoder+based+anomaly+detection+using+reconstruction+probability&rft.volume=2&rft.issue=1&rft.pages=1-18&rft.date=2015&rft.aulast=An&rft.aufirst=J.&rft.au=Cho%2C+S.&rft_id=http%3A%2F%2Fdm.snu.ac.kr%2Fstatic%2Fdocs%2FTR%2FSNUDM-TR-2015-03.pdf&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-37"><span class="mw-cite-backlink"><b><a href="#cite_ref-37">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFMalhotraVigShroffAgarwal2015" class="citation conference cs1">Malhotra, Pankaj; Vig, Lovekesh; Shroff, Gautman; Agarwal, Puneet (22–24 April 2015). <a rel="nofollow" class="external text" href="https://www.researchgate.net/publication/304782562"><i>Long Short Term Memory Networks for Anomaly Detection in Time Series</i></a>. ESANN 2015: 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. pp. 89–94. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-2-87587-015-5" title="Special:BookSources/978-2-87587-015-5"><bdi>978-2-87587-015-5</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=conference&rft.btitle=Long+Short+Term+Memory+Networks+for+Anomaly+Detection+in+Time+Series&rft.pages=89-94&rft.date=2015-04-22%2F2015-04-24&rft.isbn=978-2-87587-015-5&rft.aulast=Malhotra&rft.aufirst=Pankaj&rft.au=Vig%2C+Lovekesh&rft.au=Shroff%2C+Gautman&rft.au=Agarwal%2C+Puneet&rft_id=https%3A%2F%2Fwww.researchgate.net%2Fpublication%2F304782562&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-38"><span class="mw-cite-backlink"><b><a href="#cite_ref-38">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFHubertDebruyneRousseeuw2018" class="citation journal cs1"><a href="/wiki/Mia_Hubert" title="Mia Hubert">Hubert, Mia</a>; Debruyne, Michiel; <a href="/wiki/Peter_J._Rousseeuw" class="mw-redirect" title="Peter J. Rousseeuw">Rousseeuw, Peter J.</a> (2018). <a rel="nofollow" class="external text" href="https://doi.org/10.1002%2Fwics.1421">"Minimum covariance determinant and extensions"</a>. <i>WIREs Computational Statistics</i>. <b>10</b> (3). <a href="/wiki/ArXiv_(identifier)" class="mw-redirect" title="ArXiv (identifier)">arXiv</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://arxiv.org/abs/1709.07045">1709.07045</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.1002%2Fwics.1421">10.1002/wics.1421</a></span>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1939-5108">1939-5108</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:67227041">67227041</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=WIREs+Computational+Statistics&rft.atitle=Minimum+covariance+determinant+and+extensions&rft.volume=10&rft.issue=3&rft.date=2018&rft_id=info%3Aarxiv%2F1709.07045&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A67227041%23id-name%3DS2CID&rft.issn=1939-5108&rft_id=info%3Adoi%2F10.1002%2Fwics.1421&rft.aulast=Hubert&rft.aufirst=Mia&rft.au=Debruyne%2C+Michiel&rft.au=Rousseeuw%2C+Peter+J.&rft_id=https%3A%2F%2Fdoi.org%2F10.1002%252Fwics.1421&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-39"><span class="mw-cite-backlink"><b><a href="#cite_ref-39">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFHubertDebruyne2010" class="citation journal cs1"><a href="/wiki/Mia_Hubert" title="Mia Hubert">Hubert, Mia</a>; Debruyne, Michiel (2010). <a rel="nofollow" class="external text" href="https://onlinelibrary.wiley.com/doi/abs/10.1002/wics.61">"Minimum covariance determinant"</a>. <i>WIREs Computational Statistics</i>. <b>2</b> (1): 36–43. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1002%2Fwics.61">10.1002/wics.61</a>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1939-0068">1939-0068</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:123086172">123086172</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=WIREs+Computational+Statistics&rft.atitle=Minimum+covariance+determinant&rft.volume=2&rft.issue=1&rft.pages=36-43&rft.date=2010&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A123086172%23id-name%3DS2CID&rft.issn=1939-0068&rft_id=info%3Adoi%2F10.1002%2Fwics.61&rft.aulast=Hubert&rft.aufirst=Mia&rft.au=Debruyne%2C+Michiel&rft_id=https%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2Fabs%2F10.1002%2Fwics.61&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-40"><span class="mw-cite-backlink"><b><a href="#cite_ref-40">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFAlzubaidiZhangHumaidiAl-Dujaili2021" class="citation journal cs1">Alzubaidi, Laith; Zhang, Jinglan; Humaidi, Amjad J.; Al-Dujaili, Ayad; Duan, Ye; Al-Shamma, Omran; Santamaría, J.; Fadhel, Mohammed A.; Al-Amidie, Muthana; Farhan, Laith (2021-03-31). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010506">"Review of deep learning: concepts, CNN architectures, challenges, applications, future directions"</a>. <i>Journal of Big Data</i>. <b>8</b> (1): 53. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.1186%2Fs40537-021-00444-8">10.1186/s40537-021-00444-8</a></span>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/2196-1115">2196-1115</a>. <a href="/wiki/PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010506">8010506</a></span>. <a href="/wiki/PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/33816053">33816053</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Journal+of+Big+Data&rft.atitle=Review+of+deep+learning%3A+concepts%2C+CNN+architectures%2C+challenges%2C+applications%2C+future+directions&rft.volume=8&rft.issue=1&rft.pages=53&rft.date=2021-03-31&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC8010506%23id-name%3DPMC&rft.issn=2196-1115&rft_id=info%3Apmid%2F33816053&rft_id=info%3Adoi%2F10.1186%2Fs40537-021-00444-8&rft.aulast=Alzubaidi&rft.aufirst=Laith&rft.au=Zhang%2C+Jinglan&rft.au=Humaidi%2C+Amjad+J.&rft.au=Al-Dujaili%2C+Ayad&rft.au=Duan%2C+Ye&rft.au=Al-Shamma%2C+Omran&rft.au=Santamar%C3%ADa%2C+J.&rft.au=Fadhel%2C+Mohammed+A.&rft.au=Al-Amidie%2C+Muthana&rft.au=Farhan%2C+Laith&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC8010506&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-41"><span class="mw-cite-backlink"><b><a href="#cite_ref-41">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFBelayBlaksethRasheedSalvo_Rossi2023" class="citation journal cs1">Belay, Mohammed Ayalew; Blakseth, Sindre Stenen; Rasheed, Adil; Salvo Rossi, Pierluigi (January 2023). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007300">"Unsupervised Anomaly Detection for IoT-Based Multivariate Time Series: Existing Solutions, Performance Analysis and Future Directions"</a>. <i>Sensors</i>. <b>23</b> (5): 2844. <a href="/wiki/Bibcode_(identifier)" class="mw-redirect" title="Bibcode (identifier)">Bibcode</a>:<a rel="nofollow" class="external text" href="https://ui.adsabs.harvard.edu/abs/2023Senso..23.2844B">2023Senso..23.2844B</a>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.3390%2Fs23052844">10.3390/s23052844</a></span>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1424-8220">1424-8220</a>. <a href="/wiki/PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007300">10007300</a></span>. <a href="/wiki/PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/36905048">36905048</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Sensors&rft.atitle=Unsupervised+Anomaly+Detection+for+IoT-Based+Multivariate+Time+Series%3A+Existing+Solutions%2C+Performance+Analysis+and+Future+Directions&rft.volume=23&rft.issue=5&rft.pages=2844&rft.date=2023-01&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC10007300%23id-name%3DPMC&rft_id=info%3Abibcode%2F2023Senso..23.2844B&rft_id=info%3Apmid%2F36905048&rft_id=info%3Adoi%2F10.3390%2Fs23052844&rft.issn=1424-8220&rft.aulast=Belay&rft.aufirst=Mohammed+Ayalew&rft.au=Blakseth%2C+Sindre+Stenen&rft.au=Rasheed%2C+Adil&rft.au=Salvo+Rossi%2C+Pierluigi&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC10007300&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-42"><span class="mw-cite-backlink"><b><a href="#cite_ref-42">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFHeXuDeng2003" class="citation journal cs1">He, Z.; Xu, X.; Deng, S. (2003). "Discovering cluster-based local outliers". <i>Pattern Recognition Letters</i>. <b>24</b> (9–10): 1641–1650. <a href="/wiki/Bibcode_(identifier)" class="mw-redirect" title="Bibcode (identifier)">Bibcode</a>:<a rel="nofollow" class="external text" href="https://ui.adsabs.harvard.edu/abs/2003PaReL..24.1641H">2003PaReL..24.1641H</a>. <a href="/wiki/CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.4242">10.1.1.20.4242</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1016%2FS0167-8655%2803%2900003-5">10.1016/S0167-8655(03)00003-5</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Pattern+Recognition+Letters&rft.atitle=Discovering+cluster-based+local+outliers&rft.volume=24&rft.issue=9%E2%80%9310&rft.pages=1641-1650&rft.date=2003&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fsummary%3Fdoi%3D10.1.1.20.4242%23id-name%3DCiteSeerX&rft_id=info%3Adoi%2F10.1016%2FS0167-8655%2803%2900003-5&rft_id=info%3Abibcode%2F2003PaReL..24.1641H&rft.aulast=He&rft.aufirst=Z.&rft.au=Xu%2C+X.&rft.au=Deng%2C+S.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-43"><span class="mw-cite-backlink"><b><a href="#cite_ref-43">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFCampelloMoulaviZimekSander2015" class="citation journal cs1">Campello, R. J. G. B.; Moulavi, D.; <a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, A.</a>; Sander, J. (2015). "Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection". <i>ACM Transactions on Knowledge Discovery from Data</i>. <b>10</b> (1): 5:1–51. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F2733381">10.1145/2733381</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:2887636">2887636</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=ACM+Transactions+on+Knowledge+Discovery+from+Data&rft.atitle=Hierarchical+Density+Estimates+for+Data+Clustering%2C+Visualization%2C+and+Outlier+Detection&rft.volume=10&rft.issue=1&rft.pages=5%3A1-51&rft.date=2015&rft_id=info%3Adoi%2F10.1145%2F2733381&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A2887636%23id-name%3DS2CID&rft.aulast=Campello&rft.aufirst=R.+J.+G.+B.&rft.au=Moulavi%2C+D.&rft.au=Zimek%2C+A.&rft.au=Sander%2C+J.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-44"><span class="mw-cite-backlink"><b><a href="#cite_ref-44">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFLazarevicKumar2005" class="citation book cs1">Lazarevic, A.; Kumar, V. (2005). "Feature bagging for outlier detection". <i>Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining</i>. pp. 157–166. <a href="/wiki/CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.399.425">10.1.1.399.425</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F1081870.1081891">10.1145/1081870.1081891</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-59593-135-1" title="Special:BookSources/978-1-59593-135-1"><bdi>978-1-59593-135-1</bdi></a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:2054204">2054204</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.atitle=Feature+bagging+for+outlier+detection&rft.btitle=Proceedings+of+the+eleventh+ACM+SIGKDD+international+conference+on+Knowledge+discovery+in+data+mining&rft.pages=157-166&rft.date=2005&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fsummary%3Fdoi%3D10.1.1.399.425%23id-name%3DCiteSeerX&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A2054204%23id-name%3DS2CID&rft_id=info%3Adoi%2F10.1145%2F1081870.1081891&rft.isbn=978-1-59593-135-1&rft.aulast=Lazarevic&rft.aufirst=A.&rft.au=Kumar%2C+V.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-45"><span class="mw-cite-backlink"><b><a href="#cite_ref-45">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFNguyenAngGopalkrishnan2010" class="citation conference cs1">Nguyen, H. V.; Ang, H. H.; Gopalkrishnan, V. (2010). <i>Mining Outliers with Ensemble of Heterogeneous Detectors on Random Subspaces</i>. Database Systems for Advanced Applications. Lecture Notes in Computer Science. Vol. 5981. p. 368. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2F978-3-642-12026-8_29">10.1007/978-3-642-12026-8_29</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-3-642-12025-1" title="Special:BookSources/978-3-642-12025-1"><bdi>978-3-642-12025-1</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=conference&rft.btitle=Mining+Outliers+with+Ensemble+of+Heterogeneous+Detectors+on+Random+Subspaces&rft.series=Lecture+Notes+in+Computer+Science&rft.pages=368&rft.date=2010&rft_id=info%3Adoi%2F10.1007%2F978-3-642-12026-8_29&rft.isbn=978-3-642-12025-1&rft.aulast=Nguyen&rft.aufirst=H.+V.&rft.au=Ang%2C+H.+H.&rft.au=Gopalkrishnan%2C+V.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-46"><span class="mw-cite-backlink"><b><a href="#cite_ref-46">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFKriegelKrögerSchubertZimek2011" class="citation conference cs1"><a href="/wiki/Hans-Peter_Kriegel" title="Hans-Peter Kriegel">Kriegel, H. P.</a>; Kröger, P.; Schubert, E.; <a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, A.</a> (2011). <i>Interpreting and Unifying Outlier Scores</i>. Proceedings of the 2011 SIAM International Conference on Data Mining. pp. 13–24. <a href="/wiki/CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.232.2719">10.1.1.232.2719</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1137%2F1.9781611972818.2">10.1137/1.9781611972818.2</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-0-89871-992-5" title="Special:BookSources/978-0-89871-992-5"><bdi>978-0-89871-992-5</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=conference&rft.btitle=Interpreting+and+Unifying+Outlier+Scores&rft.pages=13-24&rft.date=2011&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fsummary%3Fdoi%3D10.1.1.232.2719%23id-name%3DCiteSeerX&rft_id=info%3Adoi%2F10.1137%2F1.9781611972818.2&rft.isbn=978-0-89871-992-5&rft.aulast=Kriegel&rft.aufirst=H.+P.&rft.au=Kr%C3%B6ger%2C+P.&rft.au=Schubert%2C+E.&rft.au=Zimek%2C+A.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-47"><span class="mw-cite-backlink"><b><a href="#cite_ref-47">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFSchubertWojdanowskiZimekKriegel2012" class="citation conference cs1">Schubert, E.; Wojdanowski, R.; <a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, A.</a>; <a href="/wiki/Hans-Peter_Kriegel" title="Hans-Peter Kriegel">Kriegel, H. P.</a> (2012). <i>On Evaluation of Outlier Rankings and Outlier Scores</i>. Proceedings of the 2012 SIAM International Conference on Data Mining. pp. 1047–1058. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1137%2F1.9781611972825.90">10.1137/1.9781611972825.90</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-61197-232-0" title="Special:BookSources/978-1-61197-232-0"><bdi>978-1-61197-232-0</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=conference&rft.btitle=On+Evaluation+of+Outlier+Rankings+and+Outlier+Scores&rft.pages=1047-1058&rft.date=2012&rft_id=info%3Adoi%2F10.1137%2F1.9781611972825.90&rft.isbn=978-1-61197-232-0&rft.aulast=Schubert&rft.aufirst=E.&rft.au=Wojdanowski%2C+R.&rft.au=Zimek%2C+A.&rft.au=Kriegel%2C+H.+P.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-48"><span class="mw-cite-backlink"><b><a href="#cite_ref-48">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFZimekCampelloSander2014" class="citation journal cs1"><a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, A.</a>; Campello, R. J. G. B.; Sander, J. R. (2014). "Ensembles for unsupervised outlier detection". <i>ACM SIGKDD Explorations Newsletter</i>. <b>15</b>: 11–22. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F2594473.2594476">10.1145/2594473.2594476</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:8065347">8065347</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=ACM+SIGKDD+Explorations+Newsletter&rft.atitle=Ensembles+for+unsupervised+outlier+detection&rft.volume=15&rft.pages=11-22&rft.date=2014&rft_id=info%3Adoi%2F10.1145%2F2594473.2594476&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A8065347%23id-name%3DS2CID&rft.aulast=Zimek&rft.aufirst=A.&rft.au=Campello%2C+R.+J.+G.+B.&rft.au=Sander%2C+J.+R.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-49"><span class="mw-cite-backlink"><b><a href="#cite_ref-49">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFZimekCampelloSander2014" class="citation conference cs1"><a href="/wiki/Arthur_Zimek" title="Arthur Zimek">Zimek, A.</a>; Campello, R. J. G. B.; Sander, J. R. (2014). <i>Data perturbation for outlier detection ensembles</i>. Proceedings of the 26th International Conference on Scientific and Statistical Database Management – SSDBM '14. p. 1. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F2618243.2618257">10.1145/2618243.2618257</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-4503-2722-0" title="Special:BookSources/978-1-4503-2722-0"><bdi>978-1-4503-2722-0</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=conference&rft.btitle=Data+perturbation+for+outlier+detection+ensembles&rft.pages=1&rft.date=2014&rft_id=info%3Adoi%2F10.1145%2F2618243.2618257&rft.isbn=978-1-4503-2722-0&rft.aulast=Zimek&rft.aufirst=A.&rft.au=Campello%2C+R.+J.+G.+B.&rft.au=Sander%2C+J.+R.&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-50"><span class="mw-cite-backlink"><b><a href="#cite_ref-50">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFGoldsteinDengel2012" class="citation web cs1">Goldstein, Markus; Dengel, Andreas (2012). <a rel="nofollow" class="external text" href="https://www.goldiges.de/publications/HBOS-KI-2012.pdf">"Histogram-based Outlier Score (HBOS): A fast Unsupervised Anomaly Detection Algorithm"</a> <span class="cs1-format">(PDF)</span>. <i>Personal page of Markus Goldstein</i>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=unknown&rft.jtitle=Personal+page+of+Markus+Goldstein&rft.atitle=Histogram-based+Outlier+Score+%28HBOS%29%3A+A+fast+Unsupervised+Anomaly+Detection+Algorithm&rft.date=2012&rft.aulast=Goldstein&rft.aufirst=Markus&rft.au=Dengel%2C+Andreas&rft_id=https%3A%2F%2Fwww.goldiges.de%2Fpublications%2FHBOS-KI-2012.pdf&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span> (Poster only at KI 2012 conference, not in proceedings)</span> </li> <li id="cite_note-51"><span class="mw-cite-backlink"><b><a href="#cite_ref-51">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFZhaoNasrullahLi2019" class="citation journal cs1">Zhao, Yue; Nasrullah, Zain; Li, Zheng (2019). <a rel="nofollow" class="external text" href="https://www.jmlr.org/papers/volume20/19-011/19-011.pdf">"Pyod: A python toolbox for scalable outlier detection"</a> <span class="cs1-format">(PDF)</span>. <i>Journal of Machine Learning Research</i>. <b>20</b>. <a href="/wiki/ArXiv_(identifier)" class="mw-redirect" title="ArXiv (identifier)">arXiv</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://arxiv.org/abs/1901.01588">1901.01588</a></span>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Journal+of+Machine+Learning+Research&rft.atitle=Pyod%3A+A+python+toolbox+for+scalable+outlier+detection&rft.volume=20&rft.date=2019&rft_id=info%3Aarxiv%2F1901.01588&rft.aulast=Zhao&rft.aufirst=Yue&rft.au=Nasrullah%2C+Zain&rft.au=Li%2C+Zheng&rft_id=https%3A%2F%2Fwww.jmlr.org%2Fpapers%2Fvolume20%2F19-011%2F19-011.pdf&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> <li id="cite_note-52"><span class="mw-cite-backlink"><b><a href="#cite_ref-52">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="https://reference.wolfram.com/language/ref/FindAnomalies.html">"FindAnomalies"</a>. <i>Mathematica documentation</i>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=unknown&rft.jtitle=Mathematica+documentation&rft.atitle=FindAnomalies&rft_id=https%3A%2F%2Freference.wolfram.com%2Flanguage%2Fref%2FFindAnomalies.html&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAnomaly+detection" class="Z3988"></span></span> </li> </ol></div> <div class="navbox-styles"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1129693374"><style data-mw-deduplicate="TemplateStyles:r1236075235">.mw-parser-output .navbox{box-sizing:border-box;border:1px solid #a2a9b1;width:100%;clear:both;font-size:88%;text-align:center;padding:1px;margin:1em auto 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<li><a href="/wiki/Arbitrary_code_execution" title="Arbitrary code execution">Arbitrary code execution</a></li> <li><a href="/wiki/Backdoor_(computing)" title="Backdoor (computing)">Backdoors</a></li> <li>Bombs <ul><li><a href="/wiki/Fork_bomb" title="Fork bomb">Fork</a></li> <li><a href="/wiki/Logic_bomb" title="Logic bomb">Logic</a></li> <li><a href="/wiki/Time_bomb_(software)" title="Time bomb (software)">Time</a></li> <li><a href="/wiki/Zip_bomb" title="Zip bomb">Zip</a></li></ul></li> <li><a href="/wiki/Hardware_backdoor" title="Hardware backdoor">Hardware backdoors</a></li> <li><a href="/wiki/Code_injection" title="Code injection">Code injection</a></li> <li><a href="/wiki/Crimeware" title="Crimeware">Crimeware</a></li> <li><a href="/wiki/Cross-site_scripting" title="Cross-site scripting">Cross-site scripting</a></li> <li><a href="/wiki/Cross-site_leaks" title="Cross-site leaks">Cross-site leaks</a></li> <li><a href="/wiki/DOM_clobbering" title="DOM clobbering">DOM 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