Network intrusion detection model based on improved BP algorithm
Luo Qun1 , Liu Zhen-dong1
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12C) 1328-1331
1 Chongqing Creation Vocational College, YongChuan, Chongqing, China, 402160
With the rapid development of network, the performance of intrusion detection system that ensures the security of network information has been paid more and more attention. In order to overcome the disadvantages of RBF neural network, a novel RBF scheme based on improved particle swarm optimization is proposed, which can overcome the disadvantage of premature convergence. The experiment result shows that the proposed algorithm has better detection rate and false positive rate than traditional algorithms based on RBF, and it can provide important reference for network intrusion detection system in practice.