Some clustering-based methodology applications to anomaly intrusion detection systems

Abstract

The present paper introduces some clustering-based methodology applications to the anomaly and host-based intrusion detection. The proposed methodologies include fuzzy clustering, fuzzy clustering by local approximation of memberships and 2-means clustering algorithms. The presented anomaly-based frameworks are evaluated by simulation experiments and comparison of the obtained results.