International Journal of Advanced Research in Computer Engineering & Technology
Intrusion detection technology exists a lot of problems, such as low performance, low intelligent level, high false alarm rate, high false negative rate and so on. There is a need to develop some robust decision tree in order to produce effective decision rules from the attacked data. In this paper, ID3 decision tree classification method is used to build an effective decision tree for intrusion detection, then convert the decision tree into rules and save them into the knowledge base of Intrusion Detection System. These rules are used to judge whether the new network behavior is normal or abnormal.