57 results for “IDS”

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Research ArticleOpen accessIn the abstractREVIEW CLUSTERING MECHANISMS OF DISTRIBUTED DENIAL OF SERVICE ATTACKSWesam Bhaya, Mehdi Ebady ManaaDistributed Denial of Service attacks (DDoS) overwhelm network resources with useless or harmful packets and prevent normal users from accessing these network resources. These attacks jeopardize the confidentiality, privacy and integrity of information on the internet. Since it is very difficult to set any predefined rules to correctly identify genuine network traffic, an anomaly-based Intrusion Detection System (IDS) for network … …Journal of Computer Science, Vol. 10, Issue 10 · 26 Jun 2014 · 7,635 accessesView PDF Cite

Research ArticleOpen accessIn the abstractThe use of Random Forest Classification and K-means Clustering Algorithm for Detecting Time Stamped Signatures in the Active NetworksKamalanaban Ethala, R. Shesadri, N. G. RenganathanIn day to day information security infrastructure, intrusion detection is indispensible. Signature based intrusion detection system mechanisms are often available in detecting many types of attacks. But this mechanism alone is not sufficient in many cases. Another intrusion detection method viz K-means is employed for clustering and classifying the unlabelled data. IDS is a special embedded device or relied software … …Journal of Computer Science, Vol. 9, Issue 7 · 18 Jun 2013 · 7,496 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAn Improved Location aided Cluster Based Routing Protocol with Intrusion Detection System in Mobile Ad Hoc NetworksS. Mangai, A. TamilarasiProblem statement: Routing and security are the main challenges for ad hoc networks due to dynamic topology as well as resource constraints. A designed protocol must provide scalable routing with better security. Lack of any central coordination and shared wireless medium makes them more vulnerable to attacks than wired networks. And also resource constraints such as limited energy and size … …Journal of Computer Science, Vol. 7, Issue 4 · 4 Apr 2011 · 7,103 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEnsemble Learning for Proactive Detection of Network-Intrusion-Based Insurance FraudBenjamin Asubam Weyori, Selorm Kofi Tagbo et al.We propose an ensemble learning pipeline that proactively integrates Stacking Feature Embedding (SFE) with Principal Component Analysis (PCA) and tree-based ensembles to proactively detect insurance fraud originating from network intrusions. The main contributions are: (1) the novel integration of SFE-PCA as a meta-feature construction step for tabular network flow data; (2) a sensitivity analysis that justifies PCA reduction ratios used … …Journal of Computer Science, Vol. 22, Issue 7 · 16 Jul 2026 · 935 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Survey of Anomaly Detection Using Data Mining Methods for Hypertext Transfer Protocol Web ServicesMohsen Kakavand, Norwati Mustapha, Aida Mustapha et al.In contrast to traditional Intrusion Detection Systems (IDSs), data mining anomaly detection methods/techniques has been widely used in the domain of network traffic data for intrusion detection and cyber threat. Data mining is widely recognized as popular and important intelligent and automatic tools to assist humans in big data security analysis and anomaly detection over IDSs. In this study we … …Journal of Computer Science, Vol. 11, Issue 1 · 22 Jan 2015 · 9,252 accessesView PDF Cite

Research ArticleOpen accessIn the abstractWIRELESS MESH NETWORK CROSS-LAYER INTRUSION DETECTIONF. S. Al-Anzi, S. KhanIntrusion is something which is unsolicited activity and which might be used to interrupt the functions of wireless network. If we talk about wireless networks, having centralized monitoring policy; therefore it is very much easy to detect and eliminate intrusions efficiently. But when we look forward to wireless scenario, especially in the multi hop wireless network, intrusion activities are more … …Journal of Computer Science, Vol. 10, Issue 12 · 23 Dec 2014 · 8,278 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMULTI SCALE TIME SERIES PREDICTION FOR INTRUSION DETECTIONG. Palanivel, K. DuraiswamyWe propose an anomaly-based network intrusion detection system, which analyzes traffic features to detect anomalies. The proposed system can be used both in online as well as off-line mode for detecting deviations from the expected behavior. Although our approach uses network packet or flow data, it is general enough to be adaptable for use with any other network variable, which … …American Journal of Applied Sciences, Vol. 11, Issue 8 · 27 Jun 2014 · 6,776 accessesView PDF Cite