Author:("Khan, Latifur")

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(0.011s) <span class="p13n-search" data-search> <button class="btn btn-p13n save-search open-p13n-modal">Save search</button> </span> </h1> <div class="main col"> <div class="col-spacing"> <div class="search-content border shadow"> <div class="search-result-header clearfix"> <div class="clearfix"> <div class="sort-results"> <form action="https://content.iospress.com:443/search" id="sort-form"> <label class="label" for="search-sort-by"> Sort by: </label> <input name="q" type="hidden" value="author:("Khan, Latifur")" /> <div class="select select-style-sleek sort-by-display"> <select id="search-sort-by" class="sub-tabs select-sort-by custom-select" name="order"> <option value="" selected>Relevance</option> <option value="dc_issued" >Most recent</option> </select> </div> <button class="no-js">Submit</button> </form> </div> </div> <div class="search-results-bulk-action bulk-action clearfix"> <button id="mark-toggle" class="btn-link mark-toggle"><i class="icon-check-empty" id="mark-all"></i><span> Mark all</span></button> <form class="add-to-cart-form add-marked-to-cart" action="https://content.iospress.com:443/cart/add" method="post"> <input type="hidden" name="dest" value="https://content.iospress.com/search?q=author%3A%28%22Khan%2C+Latifur%22%29" /> <button class="btn btn-link btn-cart add-multiple disabled" disabled>Add marked to cart</button> </form> <form class="add-marked get-citation" method="post"> <button class="btn btn-link cite-multiple disabled" disabled>Export marked citations</button> </form> </div> </div> <div id="article-list"> <div class='result-item-wrapper'> <div class="result-item dc_type-journal-article " data-itemid="journal-of-integrated-design-and-process-science/jid16-2-04"> <div class="result-item-header"> <button class="icon-check-empty toggle-selection" data-cite-id="journal-of-integrated-design-and-process-science/jid16-2-04" data-itemid="ArticleId_jid16-2-04"><span class="visuallyhidden">Select this result for bulk action</span></button> <h2 class="result-item-title book-title" data-p13n="journal-article" data-p13n-uri="https://content.iospress.com:443/articles/journal-of-integrated-design-and-process-science/jid16-2-04" data-p13n-articleid="journal-of-integrated-design-and-process-science/jid16-2-04" data-p13n-title=" Design and Implementation of a Data Mining System for Malware Detection "   <a href="https://content.iospress.com:443/articles/journal-of-integrated-design-and-process-science/jid16-2-04?resultNumber=0&totalResults=3&start=0&q=author%3A%28%22Khan%2C+Latifur%22%29&resultsPageSize=10&rows=10"> Design and Implementation of a Data Mining System for Malware Detection </a> </h2> </div> <div class="front-meta-data"> <p class="metadata-entry"><span class="generated">Authors: </span> <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Thuraisingham%2C+Bhavani%22%29">Thuraisingham, Bhavani</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Al-Khatib%2C+Tahseen%22%29">Al-Khatib, Tahseen</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Khan%2C+Latifur%22%29">Khan, Latifur</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Masud%2C%2C+Mehedy%22%29">Masud,, Mehedy</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Hamlen%2C+Kevin%22%29">Hamlen, Kevin</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Khadilkar%2C+Vaibhav%22%29">Khadilkar, Vaibhav</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Abrol%2C+Satyen%22%29">Abrol, Satyen</a> </p> <p class="metadata-entry"><span class="generated">Article Type:</span> Research Article </p> <p class="metadata-entry"> <span class="generated">Abstract: </span> <span>This paper describes the design and implementation of a data mining system called SNODMAL (Stream based novel class detection for malware) for malware detection. SNODMAL extends our data mining system called SNOD (Stream-based Novel Class Detection) for detecting malware. SNOD is a powerful system as it can detect novel classes. We also describe the design of SNODMAL++ which is an extended version of SNODMAL.</span> </p> <p class="metadata-entry"><span class="generated">Keywords: </span> Data mining, malware detection, machine learning, stream-based novel class detection, streambased classification </p> <p class="metadata-entry"> <span class="generated">DOI: </span>10.3233/jid-2012-0016 </p> <p class="metadata-entry"><span class="generated">Citation: </span> <a href="https://content.iospress.com:443/journals/journal-of-integrated-design-and-process-science">Journal of Integrated Design & Process Science</a>, vol. 16, no. 2, pp. 33-49, 2012 </p> </div> <div class="pricing"> <strong>Price: EUR 27.50</strong> <form class="add-to-cart-form" id="add-ArticleId_jid16-2-04" action="https://content.iospress.com:443/cart/add" method="post"> <input type="hidden" name="dest" value="https://content.iospress.com/search?q=author%3A%28%22Khan%2C+Latifur%22%29" /> <input type="hidden" name="id" value="ArticleId_jid16-2-04" /> <button class="btn btn-arrow btn-cart add-single"><i class="icon-shopping-cart" role="presentation"></i> Add to cart</button> </form> </div> </div> </div> <div class='result-item-wrapper'> <div class="result-item dc_type-journal-article " data-itemid="journal-of-computer-security/jcs220130"> <div class="result-item-header"> <button class="icon-check-empty toggle-selection" data-cite-id="journal-of-computer-security/jcs220130" data-itemid="ArticleId_jcs220130"><span class="visuallyhidden">Select this result for bulk action</span></button> <h2 class="result-item-title book-title" data-p13n="journal-article" data-p13n-uri="https://content.iospress.com:443/articles/journal-of-computer-security/jcs220130" data-p13n-articleid="journal-of-computer-security/jcs220130" data-p13n-title=" Con2Mix: A semi-supervised method for imbalanced tabular security data <sup>1</sup> "   <a href="https://content.iospress.com:443/articles/journal-of-computer-security/jcs220130?resultNumber=1&totalResults=3&start=0&q=author%3A%28%22Khan%2C+Latifur%22%29&resultsPageSize=10&rows=10"> Con2Mix: A semi-supervised method for imbalanced tabular security data <sup>1</sup> </a> </h2> </div> <div class="front-meta-data"> <p class="metadata-entry"><span class="generated">Authors: </span> <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Li%2C+Xiaodi%22%29">Li, Xiaodi</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Khan%2C+Latifur%22%29">Khan, Latifur</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Zamani%2C+Mahmoud%22%29">Zamani, Mahmoud</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Wickramasuriya%2C+Shamila%22%29">Wickramasuriya, Shamila</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Hamlen%2C+Kevin%22%29">Hamlen, Kevin</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Thuraisingham%2C+Bhavani%22%29">Thuraisingham, Bhavani</a> </p> <p class="metadata-entry"><span class="generated">Article Type:</span> Research Article </p> <p class="metadata-entry"> <span class="generated">Abstract: </span> <span>Con2Mix (Contrastive Double Mixup) is a new semi-supervised learning methodology that innovates a triplet mixup data augmentation approach for finding code vulnerabilities in imbalanced, tabular security data sets. Tabular data sets in cybersecurity domains are widely known to pose challenges for machine learning because of their heavily imbalanced data (e.g., a small number of labeled attack samples buried in a sea of mostly benign, unlabeled data). Semi-supervised learning leverages a small subset of labeled data and a large subset of unlabeled data to train a learning model. While semi-supervised methods have been well studied in image and language domains, in</span> <span class="fold-elip">…</span><span class="below-fold hidden" >security domains they remain underutilized, especially on tabular security data sets which pose especially difficult contextual information loss and balance challenges for machine learning. Experiments applying Con2Mix to collected security data sets show promise for addressing these challenges, achieving state-of-the-art performance on two evaluated data sets compared with other methods. </span> <a class="view-more-abstract" href="#">Show more</a> </p> <p class="metadata-entry"><span class="generated">Keywords: </span> Semi-supervised learning, contrastive learning, tabular data sets, security data sets </p> <p class="metadata-entry"> <span class="generated">DOI: </span>10.3233/JCS-220130 </p> <p class="metadata-entry"><span class="generated">Citation: </span> <a href="https://content.iospress.com:443/journals/journal-of-computer-security">Journal of Computer Security</a>, vol. 31, no. 6, pp. 705-726, 2023 </p> </div> <div class="pricing"> <strong>Price: EUR 27.50</strong> <form class="add-to-cart-form" id="add-ArticleId_jcs220130" action="https://content.iospress.com:443/cart/add" method="post"> <input type="hidden" name="dest" value="https://content.iospress.com/search?q=author%3A%28%22Khan%2C+Latifur%22%29" /> <input type="hidden" name="id" value="ArticleId_jcs220130" /> <button class="btn btn-arrow btn-cart add-single"><i class="icon-shopping-cart" role="presentation"></i> Add to cart</button> </form> </div> </div> </div> <div class='result-item-wrapper'> <div class="result-item dc_type-journal-article " data-itemid="journal-of-computer-security/jcs230218"> <div class="result-item-header"> <button class="icon-check-empty toggle-selection" data-cite-id="journal-of-computer-security/jcs230218" data-itemid="ArticleId_jcs230218"><span class="visuallyhidden">Select this result for bulk action</span></button> <h2 class="result-item-title book-title" data-p13n="journal-article" data-p13n-uri="https://content.iospress.com:443/articles/journal-of-computer-security/jcs230218" data-p13n-articleid="journal-of-computer-security/jcs230218" data-p13n-title=" SMET: Semantic mapping of CTI reports and CVE to ATT&amp;CK for advanced threat intelligence "   <a href="https://content.iospress.com:443/articles/journal-of-computer-security/jcs230218?resultNumber=2&totalResults=3&start=0&q=author%3A%28%22Khan%2C+Latifur%22%29&resultsPageSize=10&rows=10"> SMET: Semantic mapping of CTI reports and CVE to ATT&CK for advanced threat intelligence </a> </h2> </div> <div class="front-meta-data"> <p class="metadata-entry"><span class="generated">Authors: </span> <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Abdeen%2C+Basel%22%29">Abdeen, Basel</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Al-Shaer%2C+Ehab%22%29">Al-Shaer, Ehab</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Singhal%2C+Anoop%22%29">Singhal, Anoop</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Khan%2C+Latifur%22%29">Khan, Latifur</a> | <a class="badge" href="https://content.iospress.com:443/search?q=author%3A%28%22Hamlen%2C+Kevin+W.%22%29">Hamlen, Kevin W.</a> </p> <p class="metadata-entry"><span class="generated">Article Type:</span> Research Article </p> <p class="metadata-entry"> <span class="generated">Abstract: </span> <span>With the rapid increase in the robustness and impact of cyber-attacks, a counter-evolution in defense efforts is essential to ensure a safer cyberspace. A critical aspect of cyber defense is the experts’ ability to understand, analyze, and share knowledge of attacks and vulnerabilities in a timely and intelligible manner that facilitates the detection and mitigation of emerging threats. Cyber threat intelligence (CTI) reports, and Common Vulnerabilities and Exposures (CVEs) are two primary sources of information that security analysts use to defend against cyber attacks. Analyzing the tactics, techniques, and procedures (TTPs) of attackers from these sources by mapping them to</span> <span class="fold-elip">…</span><span class="below-fold hidden" >the ATT&CK framework provides valuable insights to defenders and aids them in countering various threats. Unfortunately, due to the complexity of this mapping and the rapid growth of these frameworks, mapping CTI reports and CVEs to ATT&CK is a daunting and time-intensive undertaking. Multiple studies have proposed models that automatically achieve this mapping. However, due to their reliance on annotated datasets, these models exhibit limitations in quality and coverage. To overcome these challenges, we present SMET – a tool that automatically maps text to ATT&CK techniques based on textual similarity. SMET achieves this mapping by leveraging ATT&CK BERT, a model we trained using the SIAMESE network to learn semantic similarity among attack actions. In inference, SMET utilizes semantic extraction, ATT&CK BERT, and a logistic regression model to achieve ATT&CK mapping. As a result, SMET has demonstrated superior performance compared to other state-of-the-art models. </span> <a class="view-more-abstract" href="#">Show more</a> </p> <p class="metadata-entry"><span class="generated">Keywords: </span> Cyber threat intelligence, MITRE ATT&CK, CVE, large langauge models, deep learning, contrastive learning, SIAMESE networks </p> <p class="metadata-entry"> <span class="generated">DOI: </span>10.3233/JCS-230218 </p> <p class="metadata-entry"><span class="generated">Citation: </span> <a href="https://content.iospress.com:443/journals/journal-of-computer-security">Journal of Computer Security</a>, vol. Pre-press, no. 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Author:("Khan, Latifur") - IOS Press