A hybrid approach for intrusion-detection based on fuzzy GNP and probabilistic classification
Sagar Bhilaji Shinde, Vivek Kshirsagar, Mansi Deshmukh · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
An intrusion detection system (IDS) inspects all inbound and outbound network activity and identifies suspicious patterns that may indicate a network or system attack from someone attempting to break into or compromise a system. Intrusion detection systems, which can effectively detect intrusion accesses, have attracted attention. Our work describes a novel fuzzy genetic network programming (GNP) and probabilistic classification for detecting network intrusions.Proposed method can be flexibly applied to both misuse and anomaly detection in network-intrusion-detection problems.Examples and experimental results using intrusion detection datasets DARPA99 from MIT Lincoln Laboratory demonstrate the potential of the approach.