An intrusion detection system based on RBF neural network

Based on the information system of Shanhua Company, this paper discusses the structure and function of intrusion detection system based on RBF, the steps and method of intrusion detection. In the experiment of network simulation, through continuous training of input normal samples and abnormal sample, keeping an eye on if the RBF neural networks can distinguish the known intrusion behavior character among the training samples with high exactness and distinguish new intrusion behavior character and mutation of known intrusion behavior character with some probability. The result of experiment proves that RBF network is better than BP network in its property of optimal approximation, classify ability and the rapidity of study, RBF can improve the detection performances of IDS.