A study on fuzzy intrusion detection
Jing T. Yao, Song L. Zhao, Larry V. Saxton · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Current intrusion detection techniques mainly focus on discovering abnormal system events in computer networks and distributed communication systems. Clustering techniques are normally utilized to determine a possible attack. Due to the uncertainty nature of intrusions, fuzzy sets play an important role in recognizing dangerous events and reducing false alarms level. This paper proposes a dynamic approach that tries to discover known or unknown intrusion patterns. A dynamic fuzzy boundary is developed from labelled data for different levels of security needs. Using a set of experiment, we show the applicability of the approach.