A Study on Fingerprinting of Locally Assigned MAC-Addresses

Abstract: The number of WiFi Devices is increasing every day, most people traveling hasa device with a WiFi network card enabled. This is something EffectSoft AB in Halmstad utilizes in their service Flow, to track and count devices. The accuracy of counted devices was however not accurate enough for a commercial use and this is where this candidate Thesis will continue research on how to improve the accuracy. It introduces the fundamental problem on how one cannot directly count transmitted MAC-Addresses to count present devices, since the manufacturers implement features against this such as MAC-Address randomization. It covers how manufacturers are not consistent in their implementation of the IEEE 802.11 standard, how this can be utilized to estimate how many devices are present in the networkwith three different approaches. It also concludes that Control Frame Attacks is not a viable approach any longer to count devices and the best method for counting devices are a combination of Passive Probe Request Analysis techniques.