Performance Analysis Between EOTI-K-Means++, EOTI, and KNN for Brute Force Detection System

Bintang Nuralamsyah, Sherly Rosa Anggraeni, Labba Awwabi, Narandha Arya Ranggianto, Hudan Studiawan, Ary Mazharuddin Shiddiqi

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

1 Citation (Scopus)

Abstract

An Intrusion Detection System (IDS) is software or hardware that monitors system or network activities for policy violations or malicious activity and sends reports to the management system. Clustering algorithms using instance-based learning, such as quick, efficient optimal triangle-inequality-based EOTI can be used to discover anomalous traffic patterns. Instead of using the standard K-Means technique in the EOTI algorithm, this study uses the K-Means++ approach for clustering as EOTI-K-Means++. The K-Means++ tries to solve the K-Means algorithm's disadvantages, namely its high memory usage. For further analysis, we use k-nearest neighbors (KNN) in this problem. The K-Means++ ensures a more intelligent introduction of centroids and enhances the clustering's nature. Both basic EOTI's accuracy and EOTI-K-Means++ are slightly lower than KNN for high precision, recall, and F1-score. But they yield the fastest time and a lowest memory consumption during training and prediction. EOTI K-Means++ outperforms in terms of execution time for training of 1267.77s, but predicting process is longer than EOTI of 149987.26s.

Original languageEnglish
Title of host publication2022 10th International Conference on Information and Communication Technology, ICoICT 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages53-58
Number of pages6
ISBN (Electronic)9781665481656
DOIs
Publication statusPublished - 2022
Event10th International Conference on Information and Communication Technology, ICoICT 2022 - Virtual, Online, Indonesia
Duration: 2 Aug 20223 Aug 2022

Publication series

Name2022 10th International Conference on Information and Communication Technology, ICoICT 2022

Conference

Conference10th International Conference on Information and Communication Technology, ICoICT 2022
Country/TerritoryIndonesia
CityVirtual, Online
Period2/08/223/08/22

Keywords

  • brute force attack
  • eoti
  • intrusion detection system
  • k-nearest neighbors
  • kmeans++

Fingerprint

Dive into the research topics of 'Performance Analysis Between EOTI-K-Means++, EOTI, and KNN for Brute Force Detection System'. Together they form a unique fingerprint.

Cite this