Application of feature selection and fuzzy ARTMAP to intrusion detection

Christina B. Vilakazi, Tshilidzi Marwala

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

This paper proposes a novel approach for intrusion detection and diagnosis. The proposed approach uses Sequential Backward Floating Search for feature selection and fuzzy ARTMAP for detection and diagnosis of attacks. The optimal vigilance parameter for the fuzzy ARTMAP is chosen using a genetic algorithm. The reduced set of features decreases the computation time by 0.789s. A classification rate of 100% and 99.89% is obtained for the detection stage and diagnosis stage, respectively.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Systems, Man and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4880-4885
Number of pages6
ISBN (Print)1424401003, 9781424401000
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 IEEE International Conference on Systems, Man and Cybernetics - Taipei, Taiwan, Province of China
Duration: 8 Oct 200611 Oct 2006

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume6
ISSN (Print)1062-922X

Conference

Conference2006 IEEE International Conference on Systems, Man and Cybernetics
Country/TerritoryTaiwan, Province of China
CityTaipei
Period8/10/0611/10/06

ASJC Scopus subject areas

  • General Engineering

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