Universiti Teknologi Malaysia Institutional Repository

Hierarchical feature selection in IDS

Maarof, Mohd. Aizaini and Zainal, Anazida and Shamsuddin, Siti Mariyam (2007) Hierarchical feature selection in IDS. In: Postgraduate Annual Research Seminar (PARS’ 07), 2007, UTM, Johor Bahru.

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Abstract

Generally, IDS use all the features in network packet to evaluate and look for intrusive patterns. This data contains redundant and some give false correlation. Thus, feature selection is required to address this issue. This study integrates a statistical approach called Rough Set and evolutionary computing approach called 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:Conference or Workshop Item (Paper)
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:25370
Deposited By:INVALID USER
Deposited On:15 May 2012 07:56
Last Modified:06 Aug 2017 07:42

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