Unauthorized Radio Sensing and Privacy Risks: A Sampling Error-Based Defense

TL;DR

This paper introduces a novel sampling error-based approach using the Cramer-Rao bound to detect and mitigate unauthorized radio sensing activities that threaten individual privacy.

Contribution

It proposes a new methodology modeling pedestrian trajectories as a random process and applying CRB to evaluate and counter unauthorized sensing.

Findings

Simulation confirms accurate monitoring of unauthorized sensing in urban areas.

Proposed mitigation strategies effectively reduce privacy risks.

Method provides a quantitative framework for sensing performance evaluation.

Abstract

Unauthorized sensing activities pose an increasing threat to individual privacy, yet effective countermeasures remain underdeveloped. This paper presents a novel methodology to characterize and counter such unauthorized surveillance. We model pedestrian trajectories as a random process and leverage the Cramer-Rao bound (CRB) to evaluate sensing performance, interpreting it as sampling error within this random process. Through simulation, we verify our method's accuracy in monitoring unauthorized sensing activities in urban environments and validate the effectiveness of our proposed mitigation strategies.