Comparison between support vector machine and fuzzy Kernel C-Means as classifiers for intrusion detection system using chi-square feature selection

Zuherman Rustam, N. P.A.A. Ariantari

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

3 Citations (Scopus)

Abstract

Intrusion Detection System (IDS) has been a challenging area to be developed in recent years since there are so many kinds of network attacks that are difficult to be classified by system. Moreover, there is always the possibility of the upcoming new attack. Therefore, Intrusion detection system must be improved by new classifiers to obtain the best results not only for classifying attack but also recognizing a new type of attack in an advanced way. These developments will be beneficial for managing security systems in an upcoming era. There are several classifier algorithms for Intrusion Detection System such as Support Vector Machine (SVM) and Fuzzy Kernel C-Means (FKCM). SVM classifier is known as one of the techniques to improve efficiency in attack detection while FKCM is famous because it provides better results to reduce the number of selected data features. Each of classifiers is using kernel trick to improve the classifying matter. In this study, we will compare proposed model which are FKCM with rbf, FKCM with polynomial kernel, SVM with rbf, and SVM with polynomial kernel to find a better result that could increase the accuracy of classifying network attacks. KDD Cup 1999 will be used to evaluate each model. In this study, the use of SVM with polynomial kernel brings the best result with 100 % accuracy can be obtained in 1.9 second.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
EditorsRatna Yuniati, Terry Mart, Ivandini T. Anggraningrum, Djoko Triyono, Kiki A. Sugeng
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735417410
DOIs
Publication statusPublished - 22 Oct 2018
Event3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017 - Bali, Indonesia
Duration: 26 Jul 201727 Jul 2017

Publication series

NameAIP Conference Proceedings
Volume2023
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
CountryIndonesia
CityBali
Period26/07/1727/07/17

Keywords

  • Fuzzy Kernel C-Means (FKCM)
  • Intrusion Detection System (IDS)
  • Support Vector Machine (SVM)

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