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 â€“ ICCSA 2007. Springer Berlin / Heidelberg, pp. 512-524. ISBN 978-3-540-74468-9
Full text not available from this repository.
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|
|Deposited By:||Ms Zalinda Shuratman|
|Deposited On:||28 Oct 2008 04:06|
|Last Modified:||28 Oct 2008 04:06|
Repository Staff Only: item control page