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Design Network Intrusion Detection System using Hybrid Fuzzy-Neural Network
muna mhammad taher jawhar, Monica Mehrotra
Pages - 285 - 294     |    Revised - 30-06-2010     |    Published - 10-08-2010
Volume - 4   Issue - 3    |    Publication Date - July 2010  Table of Contents
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KEYWORDS
intrusion detection, neural network, fuzzy claustering
ABSTRACT
As networks grow both in importance and size, there is an increasing need for effective security monitors such as Network Intrusion Detection System to prevent such illicit accesses. Intrusion Detection Systems technology is an effective approach in dealing with the problems of network security. In this paper, we present an intrusion detection model based on hybrid fuzzy logic and neural network. The key idea is to take advantage of different classification abilities of fuzzy logic and neural network for intrusion detection system. The new model has ability to recognize an attack, to differentiate one attack from another i.e. classifying attack, and the most important, to detect new attacks with high detection rate and low false negative. Training and testing data were obtained from the Defense Advanced Research Projects Agency (DARPA) intrusion detection evaluation data set
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Miss muna mhammad taher jawhar
jamia millia islamia - India
muna.taher@gmail.com
Mr. Monica Mehrotra
- India


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