A Novel Deep Neural Network Model for Computer Network Intrusion Detection Considering Connection Efficiency of Network Systems

A novel deep neural network model for computer network intrusion detection considering connection efficiency of network systems is studied in this manuscript. In intrusion detection system, intrusion features and normal user behavior are defined as the parameter set, and immune genetic algorithm is introduced to search the whole measurement space to optimize the measurement parameter set. For network-based IDS, the console is installed on the host, and the detector collecting network information is installed on other hosts in the network, the novel deep neural network is integrated to construct the efficient analysis. In the experiment part, the performance is tested and in the conclusion part, the performance of the model is summarized.