Sensors are found in diverse settings, from environmental monitoring to smart homes and public surveillance systems. They often collect sensitive data, such as video recordings or movement data. Detecting unwanted, privacy-invasive sensors, usually small and concealed, poses a challenge. Although various detection approaches exist, they lack standardized testing procedures and environments, resulting in incomparable results.

This work introduces a benchmark for evaluating sensor detection methods to address this issue. This benchmark offers a standardized framework for assessing detection approaches and meets requirements for practicality and deployability. It includes sensors used in literature and commonly sold smart home devices to ensure relevance and applicability.

Three existing sensor detection approaches are tested using the defined benchmark and compared to their claimed performance. Evaluating the approaches in the benchmark resulted in a balanced accuracy of 47 % to 84 % and a recall of 0 % to 75 % in the benchmark. Their strengths and limitations are discussed, and the approaches are compared to each other. By establishing a benchmark for testing and evaluating sensor detection approaches, this work sets a precedent for standardized sensor detection methods.