Genetic algorithm combined with support vector machine for building an intrusion detection system

Sriparna Saha, Ashok Singh Sairam, Amulya Yadav, Asif Ekbal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

In this paper, we develop an intrusion detection system (IDS) based on machine learning. We employ genetic algorithm (GA) along with Support Vector Machine (SVM) for automatically determining the appropriate set of features. The idea is then developed into a fully functional IDS. Experiments of testing the IDS on the benchmark KDD CUP 99 datasets are presented. Results show encouraging performance that opens a avenue for further research.

Original languageEnglish (US)
Title of host publicationProceedings of the 2012 International Conference on Advances in Computing, Communications and Informatics, ICACCI'12
Pages566-572
Number of pages7
DOIs
StatePublished - Sep 17 2012
Event2012 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2012 - Chennai, India
Duration: Aug 3 2012Aug 5 2012

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2012 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2012
Country/TerritoryIndia
CityChennai
Period8/3/128/5/12

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Genetic algorithm combined with support vector machine for building an intrusion detection system'. Together they form a unique fingerprint.

Cite this