Universiti Teknologi Malaysia Institutional Repository

Feature selection using rough-dpso in anomaly intrusion detection

Zainal, Anazida and Maarof, Mohd. Aizaini and Shamsuddin, Siti Mariyam (2007) Feature selection using rough-dpso in anomaly intrusion detection. In: Computational science and its applications – ICCSA 2007. Springer Berlin / Heidelberg, pp. 512-524. ISBN 978-3-540-74468-9

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Official URL: http://www.springerlink.com/content/f7gg9x253q7673...


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.

Item Type:Book Section
Additional Information:book series, lecture notes in computer science
Uncontrolled Keywords:Intrusion detection, feature selection, rough set, particle swarm optimization
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:6716
Deposited By: Zalinda Shuratman
Deposited On:28 Oct 2008 04:06
Last Modified:25 Jul 2017 02:41

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