An improving Tabu search algorithm for intrusion detection

Jian Guang Wu*, Ran Tao, Zhi Yong Li

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

Utilizing feature selection in intrusion detection can remove redundant features and improve the speed of the intrusion detection system efficiently on the basis of protecting the integrity of the original data. This paper proposes a new feature selection method that is based on KNN and Tabu search algorithm. The experiment result shows that this method can remove the redundant features, and reduce the time of feature selection. This method not only guarantees the accuracy of detection but also improves the detection speed efficiently.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011
Pages435-439
Number of pages5
DOIs
Publication statusPublished - 2011
Event3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 - Shanghai, China
Duration: 6 Jan 20117 Jan 2011

Publication series

NameProceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011
Volume1

Conference

Conference3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011
Country/TerritoryChina
CityShanghai
Period6/01/117/01/11

Keywords

  • Feature relevance
  • Feature selection
  • Intrusion detection
  • Tabu search

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