关键词: 网络入侵, 特征选择, 遗传算法, 径向基函数（RBF）神经网络

Abstract: To improve network intrusion detection rate, a network intrusion detection algorithm based on RBF neural network optimized by Genetic Algorithm（GA） is proposed in this paper. Firstly, the feature and RBFNN parameters are taken as genetic algorithm individuals while the network intrusion detection rate as the evaluation function, secondly, the optimal features and parameters are selected by selection, crossover and mutation, lastly, the algorithm performance is tested by KDD 1999 data. The results from performance analysis show that the proposed algorithm can select the optimal features and parameters quickly, and improves the network intrusion detection rate.

Key words: network intrusion, feature selection, genetic algorithm, Radial Basis Function（RBF） neural network