CHI2CV: Feature Selection using Chi-Square with Cross-Validation for Intrusion Detection System

Aulia Teaku Nururrahmah*, Tohari Ahmad

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

The internet technology has become essential needs among communities. However, this digital era threatens the security of important data and information. There are irresponsible parties that attempt to send intrusion attacks on computer networks. So, we need a security system, like Intrusion Detection System (IDS). Unfortunately, the attack types are getting more and more fast growing. There needs to be an effective intrusion detection model with a high degree of accuracy, namely by selecting the best features that can be used for the attack detection process. The feature selection method that we propose is the use of the chi-square test to determine which features are the most irrelevant to be discarded. Then from the remaining features, we need to choose the best features that can optimize the performance of attack detection on computer networks. For this reason, this research proposes a combination of chi-square and cross validation. The experimental results indicate that this proposed method has a significant impact on increasing the accuracy of detection of attacks on the network, from 95.51% to 96.70%.

Original languageEnglish
Title of host publicationISDFS 2023 - 11th International Symposium on Digital Forensics and Security
EditorsAsaf Varol, Murat Karabatak, Cihan Varol, Ahad Nasab
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350336986
DOIs
Publication statusPublished - 2023
Event11th International Symposium on Digital Forensics and Security, ISDFS 2023 - TN, United States
Duration: 11 May 202312 May 2023

Publication series

NameISDFS 2023 - 11th International Symposium on Digital Forensics and Security

Conference

Conference11th International Symposium on Digital Forensics and Security, ISDFS 2023
Country/TerritoryUnited States
CityTN
Period11/05/2312/05/23

Keywords

  • Chi-Square
  • Cross-Validation
  • Feature Selection
  • Infrastructure
  • Intrusion Detection System
  • Network Security

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