Intrusion Detection Based on Fuzzy Association Rules

With the rapid development of computer network technology, network not only provides the service for the people, but also has brought many negative effects. Intrusion detection is used to solve this problem. In order to improve the speed and intensity of intrusion detection, data mining technology can be applied to intrusion detection systems. Association rules are a common method in data mining. But, it causes the sharp boundary problem. The concept of fuzzy set is better than partition method because fuzzy sets provide a smooth transition between members and non-members of a set, consequently handle the sharp boundary problem in an appropriate way. In this paper, fuzzy association rules is researched in Intrusion Detection System. And Intrusion Detection framework is designed. It outperforms other methods, especially in terms of false positive rate.