Application of an Improved Recurrent Neural Network in Network Security Situation Prediction

Jun Ping Cai; Lei Qu; Gang Chen; Jun Yang

doi:10.4028/www.scientific.net/AMR.951.173

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 951Application of an Improved Recurrent Neural...

Application of an Improved Recurrent Neural Network in Network Security Situation Prediction

Abstract:

The expansion of the network becomes size, network mode is diversification, network topology structure becomes more complex, the data traffic rises rapidly in the network, causes the network load increases, attack, fault and other unexpected network security events are more severe. Neural network to deal with nonlinear, complexity advantage of this paper, network security situation prediction based on improved recursive neural networks, experimental results show that the high efficiency of the method, results are compared with the actual values, low error, high accuracy.

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Periodical:

Advanced Materials Research (Volume 951)

Pages:

173-176

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.951.173

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Online since:

May 2014

Authors:

Jun Ping Cai, Lei Qu, Gang Chen*, Jun Yang

Keywords:

Evaluation, Network Security Situation, Prediction, Recurrent Neural Network

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* - Corresponding Author

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