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. ICCSA 2007, Lecture Notes in Computer Science Part 1 , 4705 . pp. 512-524. ISSN 0302-9743

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Official URL: https://link.springer.com/chapter/10.1007/978-3-54...


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:Article
Additional Information:ISBN 978-3-540-74468-9; Book Series : Lecture Notes in Computer Science; Computational Science and Its Applications – ICCSA 2007 International Conference, Kuala Lumpur, Malaysia, August 26-29, 2007. Proceedings, Part I.
Uncontrolled Keywords:intrusion detection, feature selection, rough set, particle swarm optimization
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:Computer Science and Information System
ID Code:5599
Deposited By: PM Mazleena Salleh
Deposited On:27 May 2008 03:42
Last Modified:12 Sep 2017 08:35

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