Ensemble Methods Classifier Comparison for Anomaly Based Intrusion Detection System on CIDDS-002 Dataset

Ainurrochman, Arianto Nugroho, Raditia Wahyuwidayat, Santi Tiodora Sianturi, Muhamad Fauzi, M. Febrianto Ramadhan, Baskoro Adi Pratomo, Ary Mazharuddin Shiddiqi

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

6 Citations (Scopus)

Abstract

With the rapid development of information technology, the network has been everywhere. This technology has brought a lot of convenience to people, but there are also some security problems. To solve these problems, many methods have been proposed, among which is intrusion detection. A lot of research has been done to find the most effective Intrusion Detection Systems. In term of detecting novel attacks, Anomaly-Based Intrusion Detection Systems has better significance than Misuse-Based Intrusion Detection Systems. The research on the datasets being used for training and testing purposes in the detection model is as important as the model. Better dataset quality can improve intrusion detection model results. This research presents the statistical analysis of labeled flow-based CIDDS-002 dataset using ensemble methods classifier. The analysis is done concerning some prominent evaluation metrics used for evaluating Intrusion Detection Systems including Detection Rate, Accuracy, and False Positive Rate. As a result, the accuracy of the Bagging (Decision Tree) is 99.71% and Bagging (Gaussian Naïve Bayes) is 67.57%.

Original languageEnglish
Title of host publicationProceedings of 2021 13th International Conference on Information and Communication Technology and System, ICTS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages62-67
Number of pages6
ISBN (Electronic)9781665440592
DOIs
Publication statusPublished - 2021
Event13th International Conference on Information and Communication Technology and System, ICTS 2021 - Virtual, Online, Indonesia
Duration: 20 Oct 202121 Oct 2021

Publication series

NameProceedings of 2021 13th International Conference on Information and Communication Technology and System, ICTS 2021

Conference

Conference13th International Conference on Information and Communication Technology and System, ICTS 2021
Country/TerritoryIndonesia
CityVirtual, Online
Period20/10/2121/10/21

Keywords

  • Accuracy
  • Anomaly-Based Intrusion Detection System
  • CIDDS
  • Detection Rate
  • Ensemble Methods

Fingerprint

Dive into the research topics of 'Ensemble Methods Classifier Comparison for Anomaly Based Intrusion Detection System on CIDDS-002 Dataset'. Together they form a unique fingerprint.

Cite this