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A Computational Intelligence for Evaluation of Intrusion Detection System
Intrusion detection system work at many levels in the network fabric and are taking the concept of security to a whole new sphere by incorporating intelligence as a tool to protect networks against un-authorized intrusions and newer forms of attack. Intrusion detection system is one of the widely used tools for defense in computer networks. In literature, plenty of research is published on Intrusion detection systems. In this paper we present a survey of intrusion detection systems. We survey the existing types, techniques and approaches of intrusion detection systems in the literature. We propose a new architecture for intrusion detection system and outline the present research challenges and issues in intrusion detection system using SVM classifiers. Finally we carry out our experiments based on our proposed methodology using DARPA (Defense advanced research projects agency) intrusion detection data set which is used for IDS evaluation.
IDS, Data Mining, Network, DARPA Data Set, SVM
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