Adaptive Neuro-Fuzzy Intrusion Detection Systems

Authors:
Sampada Chavan;Khusbu Shah;Neha Dave;Sanghamitra Mukherjee;Ajith Abraham;Sugata Sanyal
Affiliations:
-;-;-;-;-;-
Venue:
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Year:
2004

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Abstract

The Intrusion Detection System architecture commonlyused in commercial and research systems have a numberof problems that limit their configurability, scalability orefficiency. In this paper, two machine-learningparadigms, Artificial Neural Networks and FuzzyInference System, are used to design an IntrusionDetection System. SNORT is used to perform real timetraffic analysis and packet logging on IP network duringthe training phase of the system. Then a signature patterndatabase is constructed using protocol analysis andNeuro-Fuzzy learning method. Using 1998 DARPAIntrusion Detection Evaluation Data and TCP dump rawdata, the experiments are deployed and discussed.