Nature Inspired Online Real Risk Assessment Models for Security Systems
EuroISI '08 Proceedings of the 1st European Conference on Intelligence and Security Informatics
Assessing security risk to a network using a statistical model of attacker community competence
ICICS'09 Proceedings of the 11th international conference on Information and Communications Security
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Our previous research illustrated the design of fuzzy logic based online risk assessment for Distributed Intrusion Prediction and Prevention Systems (DIPPS) [3]. Based on the DIPPS sensors, instead of merely preventing the attackers or blocking traffic, we propose a fuzzy logic based online risk assessment scheme. This paper propose a Hierarchical Neuro-Fuzzy online Risk Assessment (HiNFRA)model to aid the decision making process of a DIPPS. The fine tuning of fuzzy logic based risk assessment model is achieved using a neural network learning technique. Preliminary results indicate that the neural learning technique could improve the fuzzy controller performance and make the risk assessment model more robust.