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.

Date Published: 14 March 2013
PDF: 6 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87681Y (14 March 2013); doi: 10.1117/12.2010855

Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)