Research of Neural Network Algorithm in Agent-Based Intrusion Detection System

This paper designs an Agent-based Distributed Intrusion Detection System. The DIDS system combines host-based intrusion detection and network-based intrusion detection functions. It can be used to protect large area network and have relatively good expansibility. This paper also discusses the implementation of BP neural network in intrusion detection. Because of the traditional BP NN's weakness in learning time and performance, variable learning rate BP regression neural network (batch and momentum techniques are also used) are designed. The algorithm has been tested on a network data set. The result showed that it had much better performance than traditional BP NN.