Improved Evolutionary Neural Network Algorithm and Its Applications in Intrusion Detection

The improved evolutionary neural network algorithm can evolve neural network architectures and weights simultaneously using the evolutional rule of bi-population.It can resolve the shortage of existing least part point of BP neural network.The performance and convergent precision of the improved evolutionary neural network algorithm is improved greatly.A study of application of the algorithm in intrusion detection is proposed,and establish an intrusion detected system model based on improved evolutionary neural network is established.Using KDDCUP99 data set to test assorting machine model of evolutional neural network in this model.Experiment result shows that the method gains more higher detected ratio than the method based on BP neural network and the traditional evolutionary neural network.