Detecting MAC Misbehavior of IEEE 802.11 Devices within Ultra Dense Wi-Fi Networks

Abstract

The widespread deployment of IEEE 802.11 has made it an attractive target for potential attackers. The latest IEEE 802.11 standard has introduced encryption and authentication protocols that primarily address the issues of confidentiality and access control. However, improving network availability in the presence of misbehaving stations has not been addressed in the standard. Existing research addresses the problem of detecting misbehavior in scenarios without overlapping cells. However, in real scenarios cells overlap, resulting in a challenging environment for detecting misbehavior. The contribution of this paper is the presentation and evaluation of a new method for detecting misbehavior in this environment. This method is based on an objective function that uses a broad range of symptoms. Simulationresultsindicatethatthisnewapproachisverysensitive to misbehaving stations in ultra dense networks