Research on Intrusion Detection Model Based on improved CPN algorithm

Abstract

In this paper, the clustering analysis method of intrusion detection technology is studied and analysed combined with the algorithm of Counter Propagation Networks. Based on the traditional Counter Propagation Neural Networks (CPN), this paper takes advantage of Gene Express Programming (GEP), optimize the input vector and α of the CPN network model. It overcomes the shortcoming of the network jitter, that because of the influence of the input vector on the connection weight of the Kohonen layer in the traditional CPN network algorithm. improves the convergence time of the network, and obtains a better network clustering effect, and verifies the effectiveness and superiority of the algorithm in the intrusion data analysis from the experiment.