Detecting Security Threats in Wireless LANs Using Timing and Behavioral Anomalies

With the increasing dependence on wireless LANs (WLANs), businesses and educational institutions are in need of a reliable security mechanism. The latest security protocol, the IEEE 802.11i assures rigid security for WLANs with the support of IEEE 802.1x protocol for authentication, authorization and key distribution. Nevertheless, fresh security threats are emerging often to oust these new defense mechanisms. Further, many organizations based on superficial vendor literature, believe their wireless security is sufficient enough to prevent any unauthorized access. Having wide ranging options for security configurations, users are camouflaged into deep uncertainty. This volatile state of affairs has prevented many organizations from fully deploying WLANs for their secure communication needs, though WLANs may be cost effective and flexible. In this paper, we present an anomaly based mechanism to detect both known and emerging security threats in WLANs. Our method uses both timing and behavioral anomalies. We first look for timing and/or behavior anomalies during the security association process and then use outlier based data association approaches to verify their legitimacy. The proposed concept was tested on our experimental setup and the results obtained from EAP-LEAP and EAP-PEAP authenticated hosts are presented here.