A Feature Selection Approach for Network Intrusion Detection

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...

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Main Authors: Khor, Kok-Chin, Ting, Choo-Yee, Amnuaisuk, Somnuk-Phon
Format: Conference or Workshop Item
Published: 2009
Subjects:
Online Access:http://shdl.mmu.edu.my/1938/
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author Khor, Kok-Chin
Ting, Choo-Yee
Amnuaisuk, Somnuk-Phon
author_facet Khor, Kok-Chin
Ting, Choo-Yee
Amnuaisuk, Somnuk-Phon
author_sort Khor, Kok-Chin
building MMU Institutional Repository
collection Online Access
description 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.
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format Conference or Workshop Item
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institution Multimedia University
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last_indexed 2025-11-14T18:04:22Z
publishDate 2009
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spelling mmu-19382011-09-23T03:57:38Z http://shdl.mmu.edu.my/1938/ A Feature Selection Approach for Network Intrusion Detection Khor, Kok-Chin Ting, Choo-Yee Amnuaisuk, Somnuk-Phon T Technology (General) QA75.5-76.95 Electronic computers. Computer science 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. 2009-04 Conference or Workshop Item NonPeerReviewed 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. http://dx.doi.org/10.1109/ICIME.2009.68 doi:10.1109/ICIME.2009.68 doi:10.1109/ICIME.2009.68
spellingShingle T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
Khor, Kok-Chin
Ting, Choo-Yee
Amnuaisuk, Somnuk-Phon
A Feature Selection Approach for Network Intrusion Detection
title A Feature Selection Approach for Network Intrusion Detection
title_full A Feature Selection Approach for Network Intrusion Detection
title_fullStr A Feature Selection Approach for Network Intrusion Detection
title_full_unstemmed A Feature Selection Approach for Network Intrusion Detection
title_short A Feature Selection Approach for Network Intrusion Detection
title_sort feature selection approach for network intrusion detection
topic T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/1938/
http://shdl.mmu.edu.my/1938/
http://shdl.mmu.edu.my/1938/