The research on network security detection based on improved genetic neural algorithm

被引：0

作者：

Hui-fen, Liao ^{[1
]}

机构：

[1] Jiujiang University, China

来源：

Advances in Information Sciences and Service Sciences | 2012年 / 4卷 / 13期

关键词：

Detection; Genetic algorithm; Network security; Neural network;

D O I：

10.4156/AISS.vol4.issue13.10

中图分类号：

学科分类号：

摘要：

The methods for intrusion of network is diverse, as for the attack of virus and hacker, there are some issues that the detection speed is slow and accuracy is low due to unreasonable set of initial value of traditional method. In order to improve the accuracy of network detection, a genetic algorithm is proposed to optimize RBF neural network weight value. At first, by genetic algorithm find the most reasonable weight value of RBF neutral network, then study and detect the network data by adopting optimized RBF neural network. The test indicates compared with traditional network intrusion detection algorithm, the optimized RBF neural network improves the accuracy of network intrusion data detection, accelerates the speed of network intrusion, and improve the efficiency of detection.

引用

页码：69 / 75

页数：6

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