Applications of Clustering Methods to Anomaly-Based Intrusion Detection Systems

摘要

The present paper introduces some applications of clustering methodology, namely FLAME algorithm to the behavioral analysis of the user activities, performed by a host-based intrusion detection system. The normal and anomalous activity patterns are distinguished by 2-means clustering algorithm and separated into two non-intersecting clusters. The results of the performed simulation experiments are represented as well.