With the advent of the Internet, security has become a major concern. An intrusion detection system is used to enhance the security of networks by inspecting all inbound and outbound network activities and by identifying suspicious patterns as possible intrusions. For the past two decades, many researchers are working in Intrusion Detection Systems. In recent years, anomaly detection has gained popularity with its ability to detect novel attacks. Nowadays researchers focus on applying outlier detection techniques for anomaly detection because of its promising results in identifying true attacks and in reducing false alarm rate. In this paper, some of the works which applied outlier analysis in anomaly detection is studied and their results are analyzed.

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7. Komsit Prakobphol, Justin Zhan, "A Novel Outlier Detection Scheme for Network Intrusion Detection Systems", IEEE International Conference on Information Security and Assurance, 2008.
8. Jiong Zhang, Mohammad Zulkernine, Anwar Haque, "Random-Forests-Based Network Intrusion Detection Systems", IEEE Transactions on Systems, Man, Cybernetics - Part C: Applications and Reviews, Vol. 38, No. 5, September 2008.
9. Peng Yang, Biao Huang, "Density Based Outlier Mining Algorithm with Application to Intrusion Detection", IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, 2008.
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11. Pedro Casas, Johan Mazel, Philippe Owezarski, "UNADA: Unsupervised Network Anomaly Detection Using Sub-space Outliers Ranking
12. David Kershaw, Qignag Gao, Hai Wang, "Anomaly-Based Network Intrusion Detection Using Outlier Subspace Analysis: A Case Study", Canadian AI 2001, LNAI 6657, pp. 234-239, 2011 © Springer-Verlag Berlin Heidelberg 2011.

Outlier Detection Anomaly Detection Intrusion Detection