Know Thy Quality: Assessment of Device Detection by WiFi Signals

Broadcasted WiFi traffic of mobile devices is the foundation of several estimation techniques like location tracking or crowd counting. Many pervasive applications use these techniques to infer the current state of an environment allowing better planning of resources. A vast majority of techniques use WiFi probe request frames, which contain the unique MAC address of a mobile device. This MAC address allows counting of unique devices and thus, their carriers. To ensure privacy, device manufacturers introduced MAC randomization as anonymization technique. This causes a considerable impact on the data quality of many pervasive applications as randomizing devices create fake MAC addresses. Previous works show that randomized MAC addresses can be linked to their origin device using different derandomization techniques. However, these approaches are not feasible in practice as novel randomization techniques are designed to prevent derandomization. Moreover, the frequency of WiFi probe request frames varies significantly on several factors making it difficult to estimate device presence in a timely manner. This paper assesses the challenges with probe request frames using a new data quality framework for device detection. Additionally, alternative detection methods that do not rely on probe request frames are presented. This includes a recently publicized WiFi device detection technique and a new way of detecting devices associated with a third-party network using a feature of the 802.11 protocol.