Anomaly Intrusion Detection Methods for Wireless LAN

Nowday, wireless LANs are widely deployed in various places such as corporate office conference rooms, industrial warehouses, Internet-ready classrooms, etc. However, new concerns regarding security have been raised. Intrusion detection, as the second line of defense, is an indispensable tool for highly survivable networks. In this paper two anomaly intrusion detection methods are proposed for wireless LANs. One method uses hidden Markov model to check reflector DoS attacks, another based on adaptive resonance theory, which can learn the normal behavior with unsupervised method. The advantages of the methods are that they donpsilat need attack signatures and can detect intrusion in real-time. Experiments exhibit fairly good results, the attacks being collaboratively detected immediately.