EVALUATION OF THE EFFECTIVENESS OF ANOMALY IDS BASED ON THE CLUSTERING ALGORITHM AND DATA MINING TECHNIQUES

Authors

  • Veselina Jecheva
  • Evgeniya Nikolova

Keywords:

Anomaly based IDS, 2-means clustering, classification tree, Wagner-Fischer distance, Jaccard index, Davies-Bouldin index, Dunn index, C-index

Abstract

The purpose of this paper is to examine the feasibility of clustering-based approach to anomaly-based intrusion detection systems (IDS). The examined methodology includes a 2-means clustering algorithm with and without data mining techniques, i.e. classification trees. With purpose to evaluate theeffectiveness of the methodology, Jaccard index was applied. Davies-Bouldin index, Dunn index and C-index were applied in order to compare the performance results of the two models.

Downloads

Download data is not yet available.

References

Downloads

Published

2018-05-29

Issue

Vol. 2 No. 3 (2013): Computer Sciences and Communications

Section

Computer Science and Communications - Reviewed Publications. ISSN: 1314-7846

License

Articles published in "Computer Science and Communications" Magazine are licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.  

How to Cite

EVALUATION OF THE EFFECTIVENESS OF ANOMALY IDS BASED ON THE CLUSTERING ALGORITHM AND DATA MINING TECHNIQUES. (2018). COMPUTER SCIENCES AND COMMUNICATIONS, 2(3), 24-30. https://csc.bfu.bg/index.php/CSC/article/view/173

Most read articles by the same author(s)

1 2 > >>