A Feature Selection Approach for Network Intrusion Detection


Khor, Kok-Chin and Ting, Choo-Yee and Amnuaisuk, Somnuk-Phon (2009) A Feature Selection Approach for Network Intrusion Detection. In: International Conference on Information Management and Engineering, APR 03-05, 2009, Kuala Lumpur, MALAYSIA.

Full text not available from this repository.


Processing huge amount of collected network data to identify network intrusions needs high computational cost. Reducing features in the collected data may therefore solve the problem. We proposed an approach for obtaining optimal number of features to build an efficient model for intrusion detection system (IDS). Two feature selection algorithms were involved to generate two feature sets. These two features sets were then utilized to produce a combined and a shared feature set, respectively. The shared feature set consisted of features agreed by the two feature selection algorithms and therefore considered important features for identifying intrusions. Human intervention was then conducted to find an optimal number of features in between the combined (maximum) and shared feature sets (minimum). Empirical results showed that the proposed feature set gave equivalent results compared to the feature sets generated by the selected feature selection methods, and combined feature sets.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > T Technology (General)
Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 23 Sep 2011 03:57
Last Modified: 23 Sep 2011 03:57
URII: http://shdl.mmu.edu.my/id/eprint/1938


Downloads per month over past year

View ItemEdit (login required)