NFIDS: a neuro-fuzzy intrusion detection system

Heavy reliance on the Internet and worldwide connectivity has greatly increased the potential damage that can be inflicted by remote attacks launched over the Internet. Since it is not technically feasible to build a system with no vulnerabilities, intrusion detection has become an important area of research. The neuro-fuzzy intrusion detection system (NFIDS) is an anomaly based intrusion detection system that uses fuzzy logic and neural networks to detect if malicious activity is taking place on a network. This paper describes the architecture of the NFIDS and its components. The sample fuzzy rules are developed for some kinds of attacks and the testing results with actual network data are described.