DiffLoc: WiFi Hidden Camera Localization Based on Electromagnetic Diffraction

The growing privacy risks posed by hidden WiFi cameras have prompted increasing interest in their detection and localization. However, existing localization solutions suffer from several limitations, such as requiring substantial user effort, large activity spaces, predefined parameters, and pre-collected training data. In this paper, we present DiffLoc, a novel and low-cost system that localizes hidden WiFi cameras by leveraging the fundamental physical principle of electromagnetic diffraction. When an obstacle passes through the direct path between a transmitter and a receiver, it causes a distinctive signal attenuation pattern. We theoretically analyze the feasibility of using this phenomenon for localization, identifying two critical requirements for building an unbiased diffraction localization model: symmetry and observability. To meet these requirements, DiffLoc introduces a controllable diffraction generation method. By precisely rotating a small metal plate around a passive WiFi receiver (e.g., a Raspberry Pi), the system produces a consistent and predictable diffraction "shadowing" effect. We then construct an unbiased localization model that maps this effect to the azimuth of the hidden camera. Implemented using commercially available off-the-shelf hardware, DiffLoc achieves an average angular error of 14.82° across six diverse environments and eleven different camera models, demonstrating its effectiveness. Code, implementation details, and demo are available at: https://github.com/CamLoPA/DiffLoc.