Application of Deep Learning in New Intrusion Detection System

We design a New Deep Neural Network (NDNN) model and apply it to the intrusion detection system, which is based on the feature learning experiment of the deep structure. NDNN has an outstanding characteristics of learning ability, so it can fully study the characteristics from the training data. In the output layer, NDNN identify and classify the attack and normal messages and detect intrusion attacks through the Softmax classifier. Through the simulation experiment in the KDD Cup 99 data set, this paper designs a intrusion detection system model NDNN which further improve the accuracy of the intrusion detection system and enhance the security of the network.