Network Anomalous Intrusion Detection using Fuzzy-Bayes

Abstract

Security of networking systems has been an issue since computer networks became prevalent, most especially now that Internet is changing the facie computing. Intrusions pose significant threats to the integrity, confidentiality and availability of information for the internet users. In this paper, a new approach to real-time network anomaly intrusion detection via Fuzzy-Bayesian is proposed to detect malicious activity against computer network; the framework is described to demonstrate the effectiveness of the technique. The combination of fuzzy with Bayesian classifier will improve the overall performance of Bayes based intrusion detection system (IDS). Also, the feasibility of our method is demonstrated by the experiment performed on KDD 1999 IDS data set.