This paper analyses and proposes a novel detection strategy for the 'Chameleon' WiFi AP-AP virus. Previous research has considered virus construction, likely virus behaviour and propagation methods. The research here describes development of an objective measure of virus success, the impact of product susceptibility, the acceleration of infection and the growth of the physical area covered by the virus. An important conclusion of this investigation is that the connectivity between devices in the victim population is a more significant influence on virus propagation than any other factor. The work then proposes and experimentally verifies the application of a detection method for the virus. This method utilises layer 2 management frame information which can detect the attack while maintaining user privacy and user confidentiality, a key requirement in many security solutions.
A new niche of densely populated, unprotected networks is becoming more prevalent in public areas such as Shopping Malls, defined here as independent open-access networks, which have attributes that make attack detection more challenging than in typical enterprise networks. To address these challenges, new detection systems which do not rely on knowledge of internal device state are investigated here. This paper shows that this lack of state information requires an additional metric (The exchange timeout window) for detection of WLAN Denial of Service Probe Flood attacks. Variability in this metric has a significant influence on the ability of a detection system to reliably detect the presence of attacks. A parameter selection method is proposed which is shown to provide reliability and repeatability in attack detection in WLANs. Results obtained from ongoing live trials are presented that demonstrate the importance of accurately estimating probe request and probe response timeouts in future Independent Intrusion Detection Systems.
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