A Research into Intrusion Detection Based on Improved CPN Algorithm

Combined with the neural network method,an analysis of clustering in intrusion detection technology is conducted,and the optimization of the clustering by introducing the gene expression programming is discussed based on the counter propagation networks.And an improved CPN algorithm that is applied to the intrusion detection is proposed,which can overcome the problem of the input vector affecting the connection weight value in the Kohonen of the traditional CPN and in the mean time the networks will fall into the tremble.Furthermore,much better clustering result has been obtained,and the convergence time has been increased.Finally,the validity and superiority of the presented algorithm is demonstrated by experiment in intrusion data analysis.