Intrusion Detection System Using Fuzzy Inference System

  IJCOT-book-cover
 
International Journal of Computer & Organization Trends  (IJCOT)          
 
© 2013 by IJCOT Journal
Volume-3 Issue-4                           
Year of Publication :  2013
Authors : Harikishan ,P.Srinivasulu

MLA

Harikishan, P.Srinivasulu "Intrusion Detection System Using Fuzzy Inference System" . International Journal of Computer & organization Trends (IJCOT), V3(4):59-66 Jul - Aug 2013, ISSN 2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.

Abstract—Network security consists of the provisions and policies adopted by a network administrator to prevent and monitor unauthorized access or denial of a computer network and network accessible resources. Intrusions are the activities that violate the security policy of a system. An Intrusion detection system monitors network or system activities for malicious activities or policy violations and produces reports to a management station. Previously several machine learning algorithms such as neural network ,data mining and many more have been used to detect intrusion behaviour. In the proposed system we have designed fuzzy inference approach for effectively identifying the intrusion activities within a network. The proposed system uses Sugeno Fuzzy Inference system for generation of fuzzy rules and ANFIS editor for experimentation. The experimentation and evaluation of the proposed intrusion detection system are performed with KDDCup99Dataset and we can easily detect whether the records are normal or attack one.

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Keywords— IDS,KDDCup99Dataset,FuzzyInferenceSystem,Anfis editor.