Title : 
HiNFRA: Hierarchical Neuro-Fuzzy Learning for Online Risk Assessment
         
        
            Author : 
Haslum, Kjetil ; Abraham, Ajith ; Knapskog, Svein
         
        
            Author_Institution : 
Center for Quantifiable Quality of Service in Commun. Syst., Norwegian Univ. of Sci. & Technol., Trondheim
         
        
        
        
        
            Abstract : 
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.
         
        
            Keywords : 
fuzzy logic; fuzzy neural nets; learning (artificial intelligence); risk management; security of data; DIPPS; HiNFRA; distributed intrusion prediction and prevention systems; fuzzy logic; hierarchical neuro-fuzzy learning online risk assessment; neural network learning technique; Centralized control; Fuzzy logic; Hidden Markov models; Humans; Intrusion detection; Mobile agents; Monitoring; Risk management; Telecommunication traffic; Traffic control;
         
        
        
        
            Conference_Titel : 
Modeling & Simulation, 2008. AICMS 08. Second Asia International Conference on
         
        
            Conference_Location : 
Kuala Lumpur
         
        
            Print_ISBN : 
978-0-7695-3136-6
         
        
            Electronic_ISBN : 
978-0-7695-3136-6
         
        
        
            DOI : 
10.1109/AMS.2008.120