Feature selection using rough-DPSO in anomaly intrusion detection

Authors:
Anazida Zainal;Mohd Aizaini Maarof;Siti Mariyam Shamsuddin
Affiliations:
Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia;Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia;Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
Venue:
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Year:
2007

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Abstract

Most of the existing IDS use all the features in network packet to evaluate and look for known intrusive patterns. Some of these features are irrelevant and redundant. The drawback to this approach is a lengthy detection process. In real-time environment this may degrade the performance of an IDS. Thus, feature selection is required to address this issue. In this paper, we use wrapper approach where we integrate Rough Set and Particle Swarm to form a 2-tier structure of feature selection process. Experimental results show that feature subset proposed by Rough-DPSO gives better representation of data and they are robust.