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Network Intrusion Detection Method Based on High Speed and Precise Genetic Algorithm Neural Network

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2 Author(s)
Jingwen Tian ; Dept. of Autom. Control, Beijing Union Univ., Beijing ; Meijuan Gao

Aimed at the network intrusion behaviors are characterized with uncertainty, complexity, diversity and dynamic tendency and the advantages of neural network, an intrusion detection method based on high speed and precise genetic algorithm neural network is presented in this paper. The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP network which has higher accuracy and faster convergence speed. We construct the network structure, and give the algorithm flow. We discussed and analyzed the impact factor of intrusion behaviors. With the ability of strong self-learning and faster convergence of high speed and precise genetic algorithm neural network, the network intrusion detection method can detect various intrusion behaviors rapidly and effectively by learning the typical intrusion characteristic information. The experimental result shows that this intrusion detection method is feasible and effective.

Published in:

Networks Security, Wireless Communications and Trusted Computing, 2009. NSWCTC '09. International Conference on  (Volume:2 )

Date of Conference:

25-26 April 2009