Neural Network-based Intrusion Detection And Realization

Nowadays,the network security question has been prominent more and more. Intrusion Detection System has become the essential security means. The so-called intrusion detection is to detect and identify the illegal attack and intrusion behavior that aim at the computer system,information system and the network. This technique has been used to protect the information of the companies in the world. .Thus,intrusion detection system is becoming a key technique in computer security.In that rule based intrusion detection techniques suffer management of rule databases and building of statistical patterns,to apply artificial neural network into intrusion detection system is proposed. Artificial neural network is popular in pattern recognition field as it deals with the classification problem well,this is just the same as how a network intrusion needs to be.In this thesis,the back propagation algorithm is deeply studied and for fastening the learning an improvement of traditional back propagation algorithm has been done. Based on the improved algorithm,a prototype of intrusion detections system is implemented. The results of experiment show that it is feasible to apply artificial neural network into intrusion detection although more improvement in the research is needed later on.