Model of Network Intrusion Detection System based on BP Algorithm

Security has become an important issue for networks. Models of network intrusion detection system are important component of the issue. The research aims at the design and implementation of an Intrusion Detection System based on BP algorithm that can promptly detect attacks, no matter they are known or not. In this model, BP algorithm is used to learn about the normal users' behavior and the abnormal users' behavior. When the learning is over, a k-matching algorithm is given. The model is tested with the network traffic that contains both normal and abnormal data. In experiments, result proves the model is effective.