MAC Address Anonymization for Crowd Counting
This addresses privacy concerns for crowd monitoring systems, but it is incremental as it builds on existing WiFi counting methods.
The paper tackled the problem of preserving privacy in WiFi-based crowd counting by anonymizing MAC addresses using a hash-based approach, showing that time-synchronization inaccuracies and hashing collision rates are low enough to not interfere with counting accuracy.
Research has shown that counting WiFi packets called probe requests (PRs) implicitly provides a proxy for the number of people in an area. In this paper, we discuss a crowd counting system involving WiFi sensors detecting PRs over the air, then extracting and anonymizing their media access control (MAC) addresses using a hash-based approach. This paper discusses an anonymization procedure and shows time-synchronization inaccuracies among sensors and hashing collision rates to be low enough to prevent anonymization from interfering with counting algorithms. In particular, we derive an approximation of the collision rate of uniformly distributed identifiers, with analytical error bounds.