Hybrid Model for Computer Intrusion Detection

摘要

The goal of intrusion detection is to discover unauthorized use of computer systems. New intrusion types, of which detection systems are unaware, are the most difficult to detect. In this paper we propose an intrusion detection method that combines rule induction analysis for misuse detection and Fuzzy c-means for anomaly detection. Rule induction is used to generate patterns from data and finding a set of rules that satisfy some predefined criteria. Fuzzy c-Means allow objects to belong to several clusters simultaneously, with different degrees of membership. Our method is an accurate model for handle complex attack patterns in large networks. We used data set from 1999 KDD intrusion detection contest.