Anomaly intrusion detection system based on neural network

Neural network can be used in anomaly detection. In order to improve the traditional IDS (intrusion detection system) performance, we often had to change the network structure itself and detection algorism. And because intrusion techniques are most changeful and unpredictable, we can not always use the fixed detection techniques to catch exactly all possible intrusions. It is therefore important to investigate novel detection methods and IDS models. In this paper, a model of intrusion detection system based on BP neural network is proposed through analyzing characteristic of program behavior. Some details and issues on the design and implementation of the model are discussed and an experiment is also given.