BFId: Identity Inference Attacks Utilizing Beamforming Feedback Information

Beamforming, as introduced in WiFi 5, requires clients to broadcast observations of their channel characteristics. This introduces a new information source for WiFi sensing with privacy threats that have not been explored, so far.
With WiFi networks being ubiquitous in our everyday lives, the impact of unknown privacy threats is likely severe.

To investigate this concern, we introduce BFId, the first identity inference attack using BFI-based sensing and evaluate its efficacy on a novel dataset containing WiFi recordings of 197 individuals.
We show that we can infer the identity of individuals with very high accuracy, across different walking styles and perspectives, even with large sample sizes.