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Intrusion Detection Method Based on Improved Sparrow Algorithm and Optimized SVM

  • Zechao Liu*
  • , Ran Shi*
  • , Mingyu Lei
  • , Yulin Wu
  • *Corresponding author for this work
  • Harbin Engineering University
  • China Academy of Information and Communications Technology
  • School of Computer Science and Technology, Harbin Institute of Technology

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

Abstract

With the rapid growth of network data traffic, Intrusion detection systems are more and more complicated in detecting attacks and anomalies. Support Vector Machine(SVM) is a major classifier that performs consistently well for the validity of IDS on network security defense. In this paper, we propose a new SVM intrusion detection method based on improved sparrow optimization algorithm. It aims to solve the problem that sparrow search algorithm (SSA) lacks in the ability of jumping from local optimization solution. The simulation results on KDD99 data set show that our proposed method has better effects than other methods.

Original languageEnglish
Title of host publicationProceedings - 2022 4th International Conference on Data Intelligence and Security, ICDIS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages27-30
Number of pages4
ISBN (Electronic)9781665459686
DOIs
StatePublished - 2022
Externally publishedYes
Event4th International Conference on Data Intelligence and Security, ICDIS 2022 - Shenzhen, China
Duration: 24 Aug 202226 Aug 2022

Publication series

NameProceedings - 2022 4th International Conference on Data Intelligence and Security, ICDIS 2022

Conference

Conference4th International Conference on Data Intelligence and Security, ICDIS 2022
Country/TerritoryChina
CityShenzhen
Period24/08/2226/08/22

Keywords

  • Intrusion detection
  • Sparrow search Algorithm
  • Swarm intelligence optimization

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