The Development of Intrusion Detection System Based on Improved BP Neural Network

Jin Song Yuan; Yi Wang

doi:10.4028/www.scientific.net/AMR.718-720.1973

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 718-720The Development of Intrusion Detection System...

The Development of Intrusion Detection System Based on Improved BP Neural Network

Abstract:

BP neural network is a multilayer feed-forward neural network, it achieved from input to output arbitrary nonlinear mapping, and weights are adjusted by using the back propagation learning algorithm. Intrusion detection systems using the learning ability of neural network to extract the network data profile, and it also can use the neural network has the ability of self-learning and parallel processing ability, through the construction of intelligent neural network classifier to identify abnormal, so as to achieve the purpose of detecting intrusion behavior. The paper proposes the development of intrusion detection system based on improved BP neural network. Experimental results show that the proposed algorithm has high efficiency.

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Periodical:

Advanced Materials Research (Volumes 718-720)

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1973-1979

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https://doi.org/10.4028/www.scientific.net/AMR.718-720.1973

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Online since:

July 2013

Authors:

Jin Song Yuan, Yi Wang

Keywords:

BP Neural Network (BPNN), Intrusion Detection System (IDS), Networking Security

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References

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