A network intrusion detection system based on the artificial neural networks

Authors:
Wang Jing-xin;Wang Zhi-ying;Dai Kui
Affiliations:
University of Defense Technology, Changsha, China;University of Defense Technology, Changsha, China;University of Defense Technology, Changsha, China
Venue:
InfoSecu '04 Proceedings of the 3rd international conference on Information security
Year:
2004

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Abstract

To address the problem of high false alarm rate confronted by the traditional intrusion detection systems, this paper presents a new method of applying the artificial neural networks to the network intrusion detection system. We designed and implemented a network intrusion detection system based on the artificial neural networks, and then several experiments have been carried out. For the known intrusions, the false alarm rate is less than 3 percent, and, for the unknown intrusions, the false alarm rate is less than 13 percent. All of these experimental results indicate that this method is advantageous over the traditional intrusion detection methods and some other new methods suggested.