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prevention</title> <meta name="description" content="Search results for: intrusion prevention"> <meta name="keywords" content="intrusion prevention"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="intrusion prevention"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 1758</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: intrusion prevention</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1758</span> Intrusion Detection and Prevention System (IDPS) in Cloud Computing Using Anomaly-Based and Signature-Based Detection Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=John%20Onyima">John Onyima</a>, <a href="https://publications.waset.org/abstracts/search?q=Ikechukwu%20Ezepue"> Ikechukwu Ezepue</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Virtualization and cloud computing are among the fast-growing computing innovations in recent times. Organisations all over the world are moving their computing services towards the cloud this is because of its rapid transformation of the organization’s infrastructure and improvement of efficient resource utilization and cost reduction. However, this technology brings new security threats and challenges about safety, reliability and data confidentiality. Evidently, no single security technique can guarantee security or protection against malicious attacks on a cloud computing network hence an integrated model of intrusion detection and prevention system has been proposed. Anomaly-based and signature-based detection techniques will be integrated to enable the network and its host defend themselves with some level of intelligence. The anomaly-base detection was implemented using the local deviation factor graph-based (LDFGB) algorithm while the signature-based detection was implemented using the snort algorithm. Results from this collaborative intrusion detection and prevention techniques show robust and efficient security architecture for cloud computing networks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anomaly-based%20detection" title="anomaly-based detection">anomaly-based detection</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title=" cloud computing"> cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title=" intrusion detection"> intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20prevention" title=" intrusion prevention"> intrusion prevention</a>, <a href="https://publications.waset.org/abstracts/search?q=signature-based%20detection" title=" signature-based detection"> signature-based detection</a> </p> <a href="https://publications.waset.org/abstracts/89892/intrusion-detection-and-prevention-system-idps-in-cloud-computing-using-anomaly-based-and-signature-based-detection-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/89892.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">305</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1757</span> Intrusion Detection Techniques in Mobile Adhoc Networks: A Review</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashid%20Mahmood">Rashid Mahmood</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Junaid%20Sarwar"> Muhammad Junaid Sarwar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mobile ad hoc networks (MANETs) use has been well-known from the last few years in the many applications, like mission critical applications. In the (MANETS) prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in (MANETs). The authentication and encryption is considered the first solution of the MANETs problem where as now these are not sufficient as MANET use is increasing. In this paper we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in MANET and aim to comparing in some important fields. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MANET" title="MANET">MANET</a>, <a href="https://publications.waset.org/abstracts/search?q=IDS" title=" IDS"> IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusions" title=" intrusions"> intrusions</a>, <a href="https://publications.waset.org/abstracts/search?q=signature" title=" signature"> signature</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a>, <a href="https://publications.waset.org/abstracts/search?q=prevention" title=" prevention"> prevention</a> </p> <a href="https://publications.waset.org/abstracts/32173/intrusion-detection-techniques-in-mobile-adhoc-networks-a-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32173.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">378</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1756</span> Off-Policy Q-learning Technique for Intrusion Response in Network Security</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zheni%20S.%20Stefanova">Zheni S. Stefanova</a>, <a href="https://publications.waset.org/abstracts/search?q=Kandethody%20M.%20Ramachandran"> Kandethody M. Ramachandran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cyber%20security" title="cyber security">cyber security</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20prevention" title=" intrusion prevention"> intrusion prevention</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20policy" title=" optimal policy"> optimal policy</a>, <a href="https://publications.waset.org/abstracts/search?q=Q-learning" title=" Q-learning"> Q-learning</a> </p> <a href="https://publications.waset.org/abstracts/88356/off-policy-q-learning-technique-for-intrusion-response-in-network-security" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88356.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">236</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1755</span> Combination between Intrusion Systems and Honeypots</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Majed%20Sanan">Majed Sanan</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Rammal"> Mohammad Rammal</a>, <a href="https://publications.waset.org/abstracts/search?q=Wassim%20Rammal"> Wassim Rammal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Today, security is a major concern. Intrusion Detection, Prevention Systems and Honeypot can be used to moderate attacks. Many researchers have proposed to use many IDSs ((Intrusion Detection System) time to time. Some of these IDS’s combine their features of two or more IDSs which are called Hybrid Intrusion Detection Systems. Most of the researchers combine the features of Signature based detection methodology and Anomaly based detection methodology. For a signature based IDS, if an attacker attacks slowly and in organized way, the attack may go undetected through the IDS, as signatures include factors based on duration of the events but the actions of attacker do not match. Sometimes, for an unknown attack there is no signature updated or an attacker attack in the mean time when the database is updating. Thus, signature-based IDS fail to detect unknown attacks. Anomaly based IDS suffer from many false-positive readings. So there is a need to hybridize those IDS which can overcome the shortcomings of each other. In this paper we propose a new approach to IDS (Intrusion Detection System) which is more efficient than the traditional IDS (Intrusion Detection System). The IDS is based on Honeypot Technology and Anomaly based Detection Methodology. We have designed Architecture for the IDS in a packet tracer and then implemented it in real time. We have discussed experimental results performed: both the Honeypot and Anomaly based IDS have some shortcomings but if we hybridized these two technologies, the newly proposed Hybrid Intrusion Detection System (HIDS) is capable enough to overcome these shortcomings with much enhanced performance. In this paper, we present a modified Hybrid Intrusion Detection System (HIDS) that combines the positive features of two different detection methodologies - Honeypot methodology and anomaly based intrusion detection methodology. In the experiment, we ran both the Intrusion Detection System individually first and then together and recorded the data from time to time. From the data we can conclude that the resulting IDS are much better in detecting intrusions from the existing IDSs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=security" title="security">security</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title=" intrusion detection"> intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20prevention" title=" intrusion prevention"> intrusion prevention</a>, <a href="https://publications.waset.org/abstracts/search?q=honeypot" title=" honeypot"> honeypot</a>, <a href="https://publications.waset.org/abstracts/search?q=anomaly-based%20detection" title=" anomaly-based detection"> anomaly-based detection</a>, <a href="https://publications.waset.org/abstracts/search?q=signature-based%20detection" title=" signature-based detection"> signature-based detection</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title=" cloud computing"> cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=kfsensor" title=" kfsensor"> kfsensor</a> </p> <a href="https://publications.waset.org/abstracts/40174/combination-between-intrusion-systems-and-honeypots" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40174.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">382</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1754</span> Intrusion Detection Techniques in NaaS in the Cloud: A Review </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashid%20Mahmood">Rashid Mahmood</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=IDS" title="IDS">IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud" title=" cloud"> cloud</a>, <a href="https://publications.waset.org/abstracts/search?q=naas" title=" naas"> naas</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a> </p> <a href="https://publications.waset.org/abstracts/36475/intrusion-detection-techniques-in-naas-in-the-cloud-a-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36475.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1753</span> Saltwater Intrusion Studies in the Cai River in the Khanh Hoa Province, Vietnam</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Van%20Kessel">B. Van Kessel</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20T.%20Kockelkorn"> P. T. Kockelkorn</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20R.%20Speelman"> T. R. Speelman</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20C.%20Wierikx"> T. C. Wierikx</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Mai%20Van"> C. Mai Van</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20A.%20Bogaard"> T. A. Bogaard</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Saltwater intrusion is a common problem in estuaries around the world, as it could hinder the freshwater supply of coastal zones. This problem is likely to grow due to climate change and sea-level rise. The influence of these factors on the saltwater intrusion was investigated for the Cai River in the Khanh Hoa province in Vietnam. In addition, the Cai River has high seasonal fluctuations in discharge, leading to increased saltwater intrusion during the dry season. Sea level rise, river discharge changes, river mouth widening and a proposed saltwater intrusion prevention dam can have influences on the saltwater intrusion but have not been quantified for the Cai River estuary. This research used both an analytical and numerical model to investigate the effect of the aforementioned factors. The analytical model was based on a model proposed by Savenije and was calibrated using limited in situ data. The numerical model was a 3D hydrodynamic model made using the Delft3D4 software. The analytical model and numerical model agreed with in situ data, mostly for tidally average data. Both models indicated a roughly similar dependence on discharge, also agreeing that this parameter had the most severe influence on the modeled saltwater intrusion. Especially for discharges below 10 m/s3, the saltwater was predicted to reach further than 10 km. In the models, both sea-level rise and river widening mainly resulted in salinity increments up to 3 kg/m3 in the middle part of the river. The predicted sea-level rise in 2070 was simulated to lead to an increase of 0.5 km in saltwater intrusion length. Furthermore, the effect of the saltwater intrusion dam seemed significant in the model used, but only for the highest position of the gate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cai%20River" title="Cai River">Cai River</a>, <a href="https://publications.waset.org/abstracts/search?q=hydraulic%20models" title=" hydraulic models"> hydraulic models</a>, <a href="https://publications.waset.org/abstracts/search?q=river%20discharge" title=" river discharge"> river discharge</a>, <a href="https://publications.waset.org/abstracts/search?q=saltwater%20intrusion" title=" saltwater intrusion"> saltwater intrusion</a>, <a href="https://publications.waset.org/abstracts/search?q=tidal%20barriers" title=" tidal barriers"> tidal barriers</a> </p> <a href="https://publications.waset.org/abstracts/148387/saltwater-intrusion-studies-in-the-cai-river-in-the-khanh-hoa-province-vietnam" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/148387.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">111</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1752</span> Analysis and Design Modeling for Next Generation Network Intrusion Detection and Prevention System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nareshkumar%20Harale">Nareshkumar Harale</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20B.%20Meshram"> B. B. Meshram</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=network%20intrusion%20detection" title="network intrusion detection">network intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20intrusion%20prevention" title=" network intrusion prevention"> network intrusion prevention</a>, <a href="https://publications.waset.org/abstracts/search?q=association%20rule%20mining" title=" association rule mining"> association rule mining</a>, <a href="https://publications.waset.org/abstracts/search?q=system%20analysis%20and%20design" title=" system analysis and design"> system analysis and design</a> </p> <a href="https://publications.waset.org/abstracts/56014/analysis-and-design-modeling-for-next-generation-network-intrusion-detection-and-prevention-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56014.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">227</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1751</span> Real-Time Monitoring Approaches of Groundwater Conductivity and Level to Pre-Alert the Seawater Intrusion in Sand Coast of Liaodong Bay of China</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yuguang%20Wang">Yuguang Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chuanjun%20Wang"> Chuanjun Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> At present, many coastal areas around the world suffer from seawater intrusion. Seawater intrusion is the superimposed result of two factors which are nature and human social economical activities in particular area. In recent years, due to excessive exploitation of groundwater, the seawater intrusion phenomenon aggravate in coastal zone of the Bohai and Huanghai seas in our country. Moreover, with sea-level rising, the original hydrodynamic equilibrium between saltwater and freshwater has been damaged to a certain extent, and it will further aggravate seawater intrusion in the land plains. In addition, overexploitation of groundwater declined groundwater level and increase saltwater intrusion in coastal areas. Therefore, in view of the sensitivity and vulnerability of the impact of sea-level rise in the future, the risk of sea-level rise in coastal zone should be considered, reasonable exploitation, utilization and management of coastal zone’s groundwater should be formulated. The response mechanism of sea-level rise should be studied to prevent and reduce the harm of seawater intrusion, which has important theoretical and realistic significances. In this paper, through the long-term monitoring of groundwater level and conductibility in the transition region of seawater intrusion for the sand coast area, realtimely master the situation of seawater intrusion. Combined with the seasonal exploitation station of groundwater and sea level variation, early alert the seawater intrusion to prevent and reduce the harm of seawater intrusion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=groundwater%20level" title="groundwater level">groundwater level</a>, <a href="https://publications.waset.org/abstracts/search?q=sea%20level" title=" sea level"> sea level</a>, <a href="https://publications.waset.org/abstracts/search?q=seawater%20intrusion" title=" seawater intrusion"> seawater intrusion</a>, <a href="https://publications.waset.org/abstracts/search?q=sand%20coast" title=" sand coast"> sand coast</a> </p> <a href="https://publications.waset.org/abstracts/78795/real-time-monitoring-approaches-of-groundwater-conductivity-and-level-to-pre-alert-the-seawater-intrusion-in-sand-coast-of-liaodong-bay-of-china" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78795.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">469</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1750</span> Securing Web Servers by the Intrusion Detection System (IDS)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yousef%20Farhaoui">Yousef Farhaoui </a> </p> <p class="card-text"><strong>Abstract:</strong></p> An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title="intrusion detection">intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=architectures" title=" architectures"> architectures</a>, <a href="https://publications.waset.org/abstracts/search?q=characteristic" title=" characteristic"> characteristic</a>, <a href="https://publications.waset.org/abstracts/search?q=tools" title=" tools"> tools</a>, <a href="https://publications.waset.org/abstracts/search?q=security" title=" security"> security</a>, <a href="https://publications.waset.org/abstracts/search?q=web%20server" title=" web server"> web server</a> </p> <a href="https://publications.waset.org/abstracts/13346/securing-web-servers-by-the-intrusion-detection-system-ids" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13346.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">418</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1749</span> An Architecture for New Generation of Distributed Intrusion Detection System Based on Preventive Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Benmoussa">H. Benmoussa</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20A.%20El%20Kalam"> A. A. El Kalam</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Ait%20Ouahman"> A. Ait Ouahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The design and implementation of intrusion detection systems (IDS) remain an important area of research in the security of information systems. Despite the importance and reputation of the current intrusion detection systems, their efficiency and effectiveness remain limited as they should include active defense approach to allow anticipating and predicting intrusions before their occurrence. Consequently, they must be readapted. For this purpose we suggest a new generation of distributed intrusion detection system based on preventive detection approach and using intelligent and mobile agents. Our architecture benefits from mobile agent features and addresses some of the issues with centralized and hierarchical models. Also, it presents advantages in terms of increasing scalability and flexibility. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Intrusion%20Detection%20System%20%28IDS%29" title="Intrusion Detection System (IDS)">Intrusion Detection System (IDS)</a>, <a href="https://publications.waset.org/abstracts/search?q=preventive%20detection" title=" preventive detection"> preventive detection</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20agents" title=" mobile agents"> mobile agents</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20architecture" title=" distributed architecture"> distributed architecture</a> </p> <a href="https://publications.waset.org/abstracts/18239/an-architecture-for-new-generation-of-distributed-intrusion-detection-system-based-on-preventive-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18239.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">583</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1748</span> Detection of New Attacks on Ubiquitous Services in Cloud Computing and Countermeasures </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=L.%20Sellami">L. Sellami</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Idoughi"> D. Idoughi</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20F.%20Tiako"> P. F. Tiako</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cloud computing provides infrastructure to the enterprise through the Internet allowing access to cloud services at anytime and anywhere. This pervasive aspect of the services, the distributed nature of data and the wide use of information make cloud computing vulnerable to intrusions that violate the security of the cloud. This requires the use of security mechanisms to detect malicious behavior in network communications and hosts such as intrusion detection systems (IDS). In this article, we focus on the detection of intrusion into the cloud sing IDSs. We base ourselves on client authentication in the computing cloud. This technique allows to detect the abnormal use of ubiquitous service and prevents the intrusion of cloud computing. This is an approach based on client authentication data. Our IDS provides intrusion detection inside and outside cloud computing network. It is a double protection approach: The security user node and the global security cloud computing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title="cloud computing">cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection%20system" title=" intrusion detection system"> intrusion detection system</a>, <a href="https://publications.waset.org/abstracts/search?q=privacy" title=" privacy"> privacy</a>, <a href="https://publications.waset.org/abstracts/search?q=trust" title=" trust"> trust</a> </p> <a href="https://publications.waset.org/abstracts/63446/detection-of-new-attacks-on-ubiquitous-services-in-cloud-computing-and-countermeasures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63446.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">323</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1747</span> A Review of Security Attacks and Intrusion Detection Schemes in Wireless Sensor Networks: A Survey</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maleh%20Yassine">Maleh Yassine</a>, <a href="https://publications.waset.org/abstracts/search?q=Ezzati%20Abdellah"> Ezzati Abdellah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless Sensor Networks (WSNs) are currently used in different industrial and consumer applications, such as earth monitoring, health related applications, natural disaster prevention, and many other areas. Security is one of the major aspects of wireless sensor networks due to the resource limitations of sensor nodes. However, these networks are facing several threats that affect their functioning and their life. In this paper we present security attacks in wireless sensor networks, and we focus on a review and analysis of the recent Intrusion Detection schemes in WSNs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wireless%20sensor%20networks" title="wireless sensor networks">wireless sensor networks</a>, <a href="https://publications.waset.org/abstracts/search?q=security%20attack" title=" security attack"> security attack</a>, <a href="https://publications.waset.org/abstracts/search?q=denial%20of%20service" title=" denial of service"> denial of service</a>, <a href="https://publications.waset.org/abstracts/search?q=IDS" title=" IDS"> IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster-based%20model" title=" cluster-based model"> cluster-based model</a>, <a href="https://publications.waset.org/abstracts/search?q=signature%20based%20IDS" title=" signature based IDS"> signature based IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20IDS" title=" hybrid IDS"> hybrid IDS</a> </p> <a href="https://publications.waset.org/abstracts/5249/a-review-of-security-attacks-and-intrusion-detection-schemes-in-wireless-sensor-networks-a-survey" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5249.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">384</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1746</span> Proposed Anticipating Learning Classifier System for Cloud Intrusion Detection (ALCS-CID)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wafa%27%20Slaibi%20Alsharafat">Wafa' Slaibi Alsharafat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=IDS" title="IDS">IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title=" cloud computing"> cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=anticipating%20classifier%20system" title=" anticipating classifier system"> anticipating classifier system</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title=" intrusion detection"> intrusion detection</a> </p> <a href="https://publications.waset.org/abstracts/18240/proposed-anticipating-learning-classifier-system-for-cloud-intrusion-detection-alcs-cid" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18240.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">474</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1745</span> Multi-Criteria Evaluation of IDS Architectures in Cloud Computing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elmahdi%20Khalil">Elmahdi Khalil</a>, <a href="https://publications.waset.org/abstracts/search?q=Saad%20Enniari"> Saad Enniari</a>, <a href="https://publications.waset.org/abstracts/search?q=Mostapha%20Zbakh"> Mostapha Zbakh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cloud computing promises to increase innovation and the velocity with witch applications are deployed, all while helping any enterprise meet most IT service needs at a lower total cost of ownership and higher return investment. As the march of cloud continues, it brings both new opportunities and new security challenges. To take advantages of those opportunities while minimizing risks, we think that Intrusion Detection Systems (IDS) integrated in the cloud is one of the best existing solutions nowadays in the field. The concept of intrusion detection was known since past and was first proposed by a well-known researcher named Anderson in 1980's. Since that time IDS's are evolving. Although, several efforts has been made in the area of Intrusion Detection systems for cloud computing environment, many attacks still prevail. Therefore, the work presented in this paper proposes a multi criteria analysis and a comparative study between several IDS architectures designated to work in a cloud computing environments. To achieve this objective, in the first place we will search in the state of the art of several consistent IDS architectures designed to work in a cloud environment. Whereas, in a second step we will establish the criteria that will be useful for the evaluation of architectures. Later, using the approach of multi criteria decision analysis Mac Beth (Measuring Attractiveness by a Categorical Based Evaluation Technique we will evaluate the criteria and assign to each one the appropriate weight according to their importance in the field of IDS architectures in cloud computing. The last step is to evaluate architectures against the criteria and collecting results of the model constructed in the previous steps. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title="cloud computing">cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20security" title=" cloud security"> cloud security</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection%2Fprevention%20system" title=" intrusion detection/prevention system"> intrusion detection/prevention system</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20decision%20analysis" title=" multi-criteria decision analysis"> multi-criteria decision analysis</a> </p> <a href="https://publications.waset.org/abstracts/21704/multi-criteria-evaluation-of-ids-architectures-in-cloud-computing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21704.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">471</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1744</span> e-Learning Security: A Distributed Incident Response Generator</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bel%20G%20Raggad">Bel G Raggad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An e-Learning setting is a distributed computing environment where information resources can be connected to any public network. Public networks are very unsecure which can compromise the reliability of an e-Learning environment. This study is only concerned with the intrusion detection aspect of e-Learning security and how incident responses are planned. The literature reported great advances in intrusion detection system (ids) but neglected to study an important ids weakness: suspected events are detected but an intrusion is not determined because it is not defined in ids databases. We propose an incident response generator (DIRG) that produces incident responses when the working ids system suspects an event that does not correspond to a known intrusion. Data involved in intrusion detection when ample uncertainty is present is often not suitable to formal statistical models including Bayesian. We instead adopt Dempster and Shafer theory to process intrusion data for the unknown event. The DIRG engine transforms data into a belief structure using incident scenarios deduced by the security administrator. Belief values associated with various incident scenarios are then derived and evaluated to choose the most appropriate scenario for which an automatic incident response is generated. This article provides a numerical example demonstrating the working of the DIRG system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20system" title="decision support system">decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20computing" title=" distributed computing"> distributed computing</a>, <a href="https://publications.waset.org/abstracts/search?q=e-Learning%20security" title=" e-Learning security"> e-Learning security</a>, <a href="https://publications.waset.org/abstracts/search?q=incident%20response" title=" incident response"> incident response</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title=" intrusion detection"> intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=security%20risk" title=" security risk"> security risk</a>, <a href="https://publications.waset.org/abstracts/search?q=statefull%20inspection" title=" statefull inspection"> statefull inspection</a> </p> <a href="https://publications.waset.org/abstracts/23292/e-learning-security-a-distributed-incident-response-generator" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23292.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">437</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1743</span> Intrusion Detection In MANET Using Game Theory</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20B.%20Kumbalavati">S. B. Kumbalavati</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20D.%20Mallapur"> J. D. Mallapur</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Y.%20Bendigeri"> K. Y. Bendigeri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A mobile Ad-hoc network (MANET) is a multihop wireless network where nodes communicate each other without any pre-deployed infrastructure. There is no central administrating unit. Hence, MANET is generally prone to many of the attacks. These attacks may alter, release or deny data. These attacks are nothing but intrusions. Intrusion is a set of actions that attempts to compromise integrity, confidentiality and availability of resources. A major issue in the design and operation of ad-hoc network is sharing the common spectrum or common channel bandwidth among all the nodes. We are performing intrusion detection using game theory approach. Game theory is a mathematical tool for analysing problems of competition and negotiation among the players in any field like marketing, e-commerce and networking. In this paper mathematical model is developed using game theory approach and intruders are detected and removed. Bandwidth utilization is estimated and comparison is made between bandwidth utilization with intrusion detection technique and without intrusion detection technique. Percentage of intruders and efficiency of the network is analysed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ad-hoc%20network" title="ad-hoc network">ad-hoc network</a>, <a href="https://publications.waset.org/abstracts/search?q=IDS" title=" IDS"> IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=game%20theory" title=" game theory"> game theory</a>, <a href="https://publications.waset.org/abstracts/search?q=sensor%20networks" title=" sensor networks"> sensor networks</a> </p> <a href="https://publications.waset.org/abstracts/6246/intrusion-detection-in-manet-using-game-theory" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6246.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">387</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1742</span> Intrusion Detection System Based on Peer to Peer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alireza%20Pour%20Ebrahimi">Alireza Pour Ebrahimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Vahid%20Abasi"> Vahid Abasi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently by the extension of internet usage, Research on the intrusion detection system takes a significant importance. Many of improvement systems prevent internal and external network attacks by providing security through firewalls and antivirus. In recently years, intrusion detection systems gradually turn from host-based systems and depend on O.S to the distributed systems which are running on multiple O.S. In this work, by considering the diversity of computer networks whit respect to structure, architecture, resource, services, users and also security goals requirement a fully distributed collaborative intrusion detection system based on peer to peer architecture is suggested. in this platform each partner device (matched device) considered as a peer-to-peer network. All transmitted information to network are visible only for device that use security scanning of a source. Experimental results show that the distributed architecture is significantly upgradeable in respect to centralized approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=network" title="network">network</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection%20system" title=" intrusion detection system"> intrusion detection system</a>, <a href="https://publications.waset.org/abstracts/search?q=peer%20to%20peer" title=" peer to peer"> peer to peer</a>, <a href="https://publications.waset.org/abstracts/search?q=internal%20and%20external%20network" title=" internal and external network "> internal and external network </a> </p> <a href="https://publications.waset.org/abstracts/25216/intrusion-detection-system-based-on-peer-to-peer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25216.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">547</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1741</span> Seawater Intrusion in the Coastal Aquifer of Wadi Nador (Algeria)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdelkader%20Hachemi%20%20%26%20Boualem%20Remini">Abdelkader Hachemi & Boualem Remini</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Seawater intrusion is a significant challenge faced by coastal aquifers in the Mediterranean basin. This study aims to determine the position of the sharp interface between seawater and freshwater in the aquifer of Wadi Nador, located in the Wilaya of Tipaza, Algeria. A numerical areal sharp interface model using the finite element method is developed to investigate the spatial and temporal behavior of seawater intrusion. The aquifer is assumed to be homogeneous and isotropic. The simulation results are compared with geophysical prospection data obtained through electrical methods in 2011 to validate the model. The simulation results demonstrate a good agreement with the geophysical prospection data, confirming the accuracy of the sharp interface model. The position of the sharp interface in the aquifer is found to be approximately 1617 meters from the sea. Two scenarios are proposed to predict the interface position for the year 2024: one without pumping and the other with pumping. The results indicate a noticeable retreat of the sharp interface position in the first scenario, while a slight decline is observed in the second scenario. The findings of this study provide valuable insights into the dynamics of seawater intrusion in the Wadi Nador aquifer. The predicted changes in the sharp interface position highlight the potential impact of pumping activities on the aquifer's vulnerability to seawater intrusion. This study emphasizes the importance of implementing measures to manage and mitigate seawater intrusion in coastal aquifers. The sharp interface model developed in this research can serve as a valuable tool for assessing and monitoring the vulnerability of aquifers to seawater intrusion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=seawater" title="seawater">seawater</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion" title=" intrusion"> intrusion</a>, <a href="https://publications.waset.org/abstracts/search?q=sharp%20interface" title=" sharp interface"> sharp interface</a>, <a href="https://publications.waset.org/abstracts/search?q=Algeria" title=" Algeria"> Algeria</a> </p> <a href="https://publications.waset.org/abstracts/174992/seawater-intrusion-in-the-coastal-aquifer-of-wadi-nador-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174992.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">74</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1740</span> A Survey on Genetic Algorithm for Intrusion Detection System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Prikhil%20Agrawal">Prikhil Agrawal</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Priyanka"> N. Priyanka</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the increase of millions of users on Internet day by day, it is very essential to maintain highly reliable and secured data communication between various corporations. Although there are various traditional security imparting techniques such as antivirus software, password protection, data encryption, biometrics and firewall etc. But still network security has become the main issue in various leading companies. So IDSs have become an essential component in terms of security, as it can detect various network attacks and respond quickly to such occurrences. IDSs are used to detect unauthorized access to a computer system. This paper describes various intrusion detection techniques using GA approach. The intrusion detection problem has become a challenging task due to the conception of miscellaneous computer networks under various vulnerabilities. Thus the damage caused to various organizations by malicious intrusions can be mitigated and even be deterred by using this powerful tool. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm%20%28GA%29" title="genetic algorithm (GA)">genetic algorithm (GA)</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection%20system%20%28IDS%29" title=" intrusion detection system (IDS)"> intrusion detection system (IDS)</a>, <a href="https://publications.waset.org/abstracts/search?q=dataset" title=" dataset"> dataset</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20security" title=" network security"> network security</a> </p> <a href="https://publications.waset.org/abstracts/71298/a-survey-on-genetic-algorithm-for-intrusion-detection-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71298.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">297</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1739</span> Intrusion Detection Based on Graph Oriented Big Data Analytics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahlem%20Abid">Ahlem Abid</a>, <a href="https://publications.waset.org/abstracts/search?q=Farah%20%20Jemili"> Farah Jemili</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Apache%20Spark%20Streaming" title="Apache Spark Streaming">Apache Spark Streaming</a>, <a href="https://publications.waset.org/abstracts/search?q=Graph" title=" Graph"> Graph</a>, <a href="https://publications.waset.org/abstracts/search?q=Intrusion%20detection" title=" Intrusion detection"> Intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=k2%20algorithm" title=" k2 algorithm"> k2 algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=Machine%20Learning" title=" Machine Learning"> Machine Learning</a>, <a href="https://publications.waset.org/abstracts/search?q=MAWILab" title=" MAWILab"> MAWILab</a>, <a href="https://publications.waset.org/abstracts/search?q=Microsoft%20Azure%20Cloud" title=" Microsoft Azure Cloud"> Microsoft Azure Cloud</a> </p> <a href="https://publications.waset.org/abstracts/127073/intrusion-detection-based-on-graph-oriented-big-data-analytics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127073.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">146</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1738</span> Constructing a Semi-Supervised Model for Network Intrusion Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tigabu%20Dagne%20Akal">Tigabu Dagne Akal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title="intrusion detection">intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20science" title=" computer science"> computer science</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a> </p> <a href="https://publications.waset.org/abstracts/3289/constructing-a-semi-supervised-model-for-network-intrusion-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3289.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">296</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1737</span> A Sharp Interface Model for Simulating Seawater Intrusion in the Coastal Aquifer of Wadi Nador (Algeria)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdelkader%20Hachemi">Abdelkader Hachemi</a>, <a href="https://publications.waset.org/abstracts/search?q=Boualem%20Remini"> Boualem Remini</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Seawater intrusion is a significant challenge faced by coastal aquifers in the Mediterranean basin. This study aims to determine the position of the sharp interface between seawater and freshwater in the aquifer of Wadi Nador, located in the Wilaya of Tipaza, Algeria. A numerical areal sharp interface model using the finite element method is developed to investigate the spatial and temporal behavior of seawater intrusion. The aquifer is assumed to be homogeneous and isotropic. The simulation results are compared with geophysical prospection data obtained through electrical methods in 2011 to validate the model. The simulation results demonstrate a good agreement with the geophysical prospection data, confirming the accuracy of the sharp interface model. The position of the sharp interface in the aquifer is found to be approximately 1617 meters from the sea. Two scenarios are proposed to predict the interface position for the year 2024: one without pumping and the other with pumping. The results indicate a noticeable retreat of the sharp interface position in the first scenario, while a slight decline is observed in the second scenario. The findings of this study provide valuable insights into the dynamics of seawater intrusion in the Wadi Nador aquifer. The predicted changes in the sharp interface position highlight the potential impact of pumping activities on the aquifer's vulnerability to seawater intrusion. This study emphasizes the importance of implementing measures to manage and mitigate seawater intrusion in coastal aquifers. The sharp interface model developed in this research can serve as a valuable tool for assessing and monitoring the vulnerability of aquifers to seawater intrusion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=seawater%20intrusion" title="seawater intrusion">seawater intrusion</a>, <a href="https://publications.waset.org/abstracts/search?q=sharp%20interface" title=" sharp interface"> sharp interface</a>, <a href="https://publications.waset.org/abstracts/search?q=coastal%20aquifer" title=" coastal aquifer"> coastal aquifer</a>, <a href="https://publications.waset.org/abstracts/search?q=algeria" title=" algeria"> algeria</a> </p> <a href="https://publications.waset.org/abstracts/173325/a-sharp-interface-model-for-simulating-seawater-intrusion-in-the-coastal-aquifer-of-wadi-nador-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173325.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">119</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1736</span> Incorporating Multiple Supervised Learning Algorithms for Effective Intrusion Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Umar%20Albalawi">Umar Albalawi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sang%20C.%20Suh"> Sang C. Suh</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinoh%20Kim"> Jinoh Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title="intrusion detection">intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=supervised%20learning" title=" supervised learning"> supervised learning</a>, <a href="https://publications.waset.org/abstracts/search?q=traffic%20classification" title=" traffic classification"> traffic classification</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20networks" title=" computer networks"> computer networks</a> </p> <a href="https://publications.waset.org/abstracts/5421/incorporating-multiple-supervised-learning-algorithms-for-effective-intrusion-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5421.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">349</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1735</span> Performance Analysis of Traffic Classification with Machine Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Htay%20Htay%20Yi">Htay Htay Yi</a>, <a href="https://publications.waset.org/abstracts/search?q=Zin%20May%20Aye"> Zin May Aye</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=false%20negative%20rate" title="false negative rate">false negative rate</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection%20system" title=" intrusion detection system"> intrusion detection system</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20methods" title=" machine learning methods"> machine learning methods</a>, <a href="https://publications.waset.org/abstracts/search?q=performance" title=" performance"> performance</a> </p> <a href="https://publications.waset.org/abstracts/133091/performance-analysis-of-traffic-classification-with-machine-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133091.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">118</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1734</span> Intrusion Detection in Computer Networks Using a Hybrid Model of Firefly and Differential Evolution Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Besharatloo">Mohammad Besharatloo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection%20system" title="intrusion detection system">intrusion detection system</a>, <a href="https://publications.waset.org/abstracts/search?q=differential%20evolution" title=" differential evolution"> differential evolution</a>, <a href="https://publications.waset.org/abstracts/search?q=firefly%20algorithm" title=" firefly algorithm"> firefly algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20tree" title=" decision tree"> decision tree</a> </p> <a href="https://publications.waset.org/abstracts/165079/intrusion-detection-in-computer-networks-using-a-hybrid-model-of-firefly-and-differential-evolution-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165079.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">91</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1733</span> Comparison of Salt-Water Intrusion into Eastern and Western Coastal Aquifers of Urmia Lake thru Over-Exploration of Groundwater Resources</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saman%20Javadi">Saman Javadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Hassan%20Mahmoudi"> Mohammad Hassan Mahmoudi</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatemeh%20Jafari"> Fatemeh Jafari</a>, <a href="https://publications.waset.org/abstracts/search?q=Aminreza%20Neshat"> Aminreza Neshat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Urmia Lake’s water level has been dropped during the past decade. Although the most common reason in studies was declared climate change, but observation of adjacent lake (like Van in Turkey) is not the same as the common reason. Most of studies were focused on climate and land use change, but groundwater resource as one of the most important element is negligible. Due to population and agriculture activities growth, exploration of groundwater resource has been increased. In as much as continued decline of water levels can lead to saltwater intrusion, reduce stream discharge near outcrop regions and threaten groundwater quality, aquifers of this region were affected by saltwater intrusion of Urmia Lake. In this research comparison of saltwater intrusion into eastern and western coastal aquifer was studied. In conclusion eastern aquifers are in a critical situation; vice versa the western ones are in a better situation. Thus applying management of groundwater operation would be necessary for eastern aquifers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coastal%20aquifer" title="coastal aquifer">coastal aquifer</a>, <a href="https://publications.waset.org/abstracts/search?q=groundwater%20over-exploration" title=" groundwater over-exploration"> groundwater over-exploration</a>, <a href="https://publications.waset.org/abstracts/search?q=saltwater%20intrusion" title=" saltwater intrusion"> saltwater intrusion</a>, <a href="https://publications.waset.org/abstracts/search?q=Urmia%20Lake" title=" Urmia Lake"> Urmia Lake</a> </p> <a href="https://publications.waset.org/abstracts/20314/comparison-of-salt-water-intrusion-into-eastern-and-western-coastal-aquifers-of-urmia-lake-thru-over-exploration-of-groundwater-resources" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20314.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">539</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1732</span> Design of an Improved Distributed Framework for Intrusion Detection System Based on Artificial Immune System and Neural Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yulin%20Rao">Yulin Rao</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhixuan%20Li"> Zhixuan Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Burra%20Venkata%20Durga%20Kumar"> Burra Venkata Durga Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Intrusion detection refers to monitoring the actions of internal and external intruders on the system and detecting the behaviours that violate security policies in real-time. In intrusion detection, there has been much discussion about the application of neural network technology and artificial immune system (AIS). However, many solutions use static methods (signature-based and stateful protocol analysis) or centralized intrusion detection systems (CIDS), which are unsuitable for real-time intrusion detection systems that need to process large amounts of data and detect unknown intrusions. This article proposes a framework for a distributed intrusion detection system (DIDS) with multi-agents based on the concept of AIS and neural network technology to detect anomalies and intrusions. In this framework, multiple agents are assigned to each host and work together, improving the system's detection efficiency and robustness. The trainer agent in the central server of the framework uses the artificial neural network (ANN) rather than the negative selection algorithm of AIS to generate mature detectors. Mature detectors can distinguish between self-files and non-self-files after learning. Our analyzer agents use genetic algorithms to generate memory cell detectors. This kind of detector will effectively reduce false positive and false negative errors and act quickly on known intrusions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20immune%20system" title="artificial immune system">artificial immune system</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20artificial%20intelligence" title=" distributed artificial intelligence"> distributed artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent" title=" multi-agent"> multi-agent</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection%20system" title=" intrusion detection system"> intrusion detection system</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a> </p> <a href="https://publications.waset.org/abstracts/152818/design-of-an-improved-distributed-framework-for-intrusion-detection-system-based-on-artificial-immune-system-and-neural-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152818.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">109</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1731</span> The Phenomenon of the Seawater Intrusion with Fresh Groundwater in the Arab Region</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kassem%20Natouf">Kassem Natouf</a>, <a href="https://publications.waset.org/abstracts/search?q=Ihab%20Jnad"> Ihab Jnad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In coastal aquifers, the interface between fresh groundwater and salty seawater may shift inland, reaching coastal wells and causing an increase in the salinity of the water they pump, putting them out of service. Many Arab coastal sites suffer from this phenomenon due to the increased pumping of coastal groundwater. This research aims to prepare a comprehensive study describing the common characteristics of the phenomenon of seawater intrusion with coastal freshwater aquifers in the Arab region, its general and specific causes and negative effects, in a way that contributes to overcoming this phenomenon, and to exchanging expertise between Arab countries in studying and analyzing it, leading to overcoming it. This research also aims to build geographical and relational databases for data, information and studies available in Arab countries about seawater intrusion with freshwater so as to provide the data and information necessary for managing groundwater resources on Arab coasts, including studying the effects of climate change on these resources and helping decision-makers in developing executive programs to overcome the seawater intrusion with groundwater. The research relied on the methodology of analysis and comparison, where the available information and data about the phenomenon in the Arab region were collected. After that, the information and data collected were studied and analyzed, and the causes of the phenomenon in each case, its results, and solutions for prevention were stated. Finally, the different cases were compared, and the common causes, results, and methods of treatment between them were deduced, and a technical report summarizing that was prepared. To overcome the phenomenon of seawater intrusion with fresh groundwater: (1) It is necessary to develop efforts to monitor the quantity and quality of groundwater on the coasts and to develop mathematical models to predict the impact of climate change, sea level rise, and human activities on coastal groundwater. (2) Over-pumping of coastal aquifers is an important cause of seawater intrusion. To mitigate this problem, Arab countries should reduce groundwater pumping and promote rainwater harvesting, surface irrigation, and water recycling practices. (3) Artificial recharge of coastal groundwater with various forms of water, whether fresh or treated, is a promising technology to mitigate the effects of seawater intrusion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coastal%20aquifers" title="coastal aquifers">coastal aquifers</a>, <a href="https://publications.waset.org/abstracts/search?q=seawater%20intrusion" title=" seawater intrusion"> seawater intrusion</a>, <a href="https://publications.waset.org/abstracts/search?q=fresh%20groundwater" title=" fresh groundwater"> fresh groundwater</a>, <a href="https://publications.waset.org/abstracts/search?q=salinity%20increase" title=" salinity increase"> salinity increase</a>, <a href="https://publications.waset.org/abstracts/search?q=Arab%20region" title=" Arab region"> Arab region</a>, <a href="https://publications.waset.org/abstracts/search?q=groundwater%20management" title=" groundwater management"> groundwater management</a>, <a href="https://publications.waset.org/abstracts/search?q=climate%20change%20effects" title=" climate change effects"> climate change effects</a>, <a href="https://publications.waset.org/abstracts/search?q=sustainable%20water%20practices" title=" sustainable water practices"> sustainable water practices</a>, <a href="https://publications.waset.org/abstracts/search?q=over-pumping" title=" over-pumping"> over-pumping</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20recharge" title=" artificial recharge"> artificial recharge</a>, <a href="https://publications.waset.org/abstracts/search?q=monitoring%20and%20modeling" title=" monitoring and modeling"> monitoring and modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20databases" title=" data databases"> data databases</a>, <a href="https://publications.waset.org/abstracts/search?q=groundwater%20resources" title=" groundwater resources"> groundwater resources</a>, <a href="https://publications.waset.org/abstracts/search?q=negative%20effects" title=" negative effects"> negative effects</a>, <a href="https://publications.waset.org/abstracts/search?q=comparative%20analysis" title=" comparative analysis"> comparative analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=technical%20report" title=" technical report"> technical report</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20scarcity" title=" water scarcity"> water scarcity</a>, <a href="https://publications.waset.org/abstracts/search?q=groundwater%20quality" title=" groundwater quality"> groundwater quality</a>, <a href="https://publications.waset.org/abstracts/search?q=decision-making" title=" decision-making"> decision-making</a>, <a href="https://publications.waset.org/abstracts/search?q=environmental%20impact" title=" environmental impact"> environmental impact</a>, <a href="https://publications.waset.org/abstracts/search?q=agricultural%20practices" title=" agricultural practices"> agricultural practices</a> </p> <a href="https://publications.waset.org/abstracts/188936/the-phenomenon-of-the-seawater-intrusion-with-fresh-groundwater-in-the-arab-region" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/188936.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">34</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1730</span> Men’s Engagement in Intimate Partner Violence (IPV) Prevention Programs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zeynep%20Turhan">Zeynep Turhan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This review emphasized the effectiveness of men’s participation, and whether non-violent (NV) boys’ and men’s perceptions of IPV prevention programs affect their involvement. Additionally, the review aimed to identify the barriers of non-engagement as well as the most effective approaches to end and prevent violence-against-women (VAW). The main goals of this assessment were to investigate 1) how NV men engage in anti-violence prevention programs that empower women, 2) what are the possible perceptions of NV men involved in prevention programs 3) how to identify effective approaches and strategies that encourage NV men to become involved in prevention programs. This critical review also included the overview of prevention programs such as The Mentors in Violence Prevention Programs (MVP), The White Ribbon Campaign (WRC), and Domestic Violence Prevention Enhancement and Leadership through Alliances (DELTA). The review recommended expanding these programs to reach more macro settings such as workplace, faith-based and other community-based organizations. Additionally, secondary and territory prevention programs need to expand through addressing the long-term effects of violence. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=engagement" title="engagement">engagement</a>, <a href="https://publications.waset.org/abstracts/search?q=non-violent%20men" title=" non-violent men"> non-violent men</a>, <a href="https://publications.waset.org/abstracts/search?q=prevention%20programs" title=" prevention programs"> prevention programs</a> </p> <a href="https://publications.waset.org/abstracts/18742/mens-engagement-in-intimate-partner-violence-ipv-prevention-programs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18742.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">416</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1729</span> Intrusion Detection Using Dual Artificial Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rana%20I.%20Abdulghani">Rana I. Abdulghani</a>, <a href="https://publications.waset.org/abstracts/search?q=Amera%20I.%20Melhum"> Amera I. Melhum</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=IDS" title="IDS">IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=SI" title=" SI"> SI</a>, <a href="https://publications.waset.org/abstracts/search?q=BP" title=" BP"> BP</a>, <a href="https://publications.waset.org/abstracts/search?q=NSL_KDD" title=" NSL_KDD"> NSL_KDD</a>, <a href="https://publications.waset.org/abstracts/search?q=PSO" title=" PSO"> PSO</a> </p> <a href="https://publications.waset.org/abstracts/26515/intrusion-detection-using-dual-artificial-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26515.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge 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