A User-Controlled Ultrasonic Obstruction Framework for Defending Against Voice Assistant and Covert Microphone Eavesdropping
Nithyashree · Aug 15, 2026
The widespread adoption of always-listening voice assistants, together with the growing availability of low-cost covert recording devices, has created two related but distinct audio privacy threats: authorized microphones that may capture more than a user intends, and unauthorized microphones that capture without consent at all. Existing defenses treat these threats in isolation. Voice-assistant privacy relies on manufacturer trust and after-the-fact data deletion, while covert device detection depends on specialized, single-technique tools that require manual expertise. This paper proposes a unified, user-controlled acoustic privacy framework built on broadband ultrasonic obstruction, an inaudible signal that disrupts the microphone hardware itself rather than the data pipeline behind it. The framework operates in two modes: a manually toggled Privacy Mode that immediately obstructs any nearby microphone, known or unknown, with activation and release fully controlled by the user; and an on-demand Bug Sweep Mode that detects unauthorized listening devices using network-traffic and optical signals available on a standard smartphone. We deliberately defer automatic, content-aware triggering, i.e. detecting sensitive conversation and obstructing without user initiation, to future work, avoiding the surveillance-to-prevent-surveillance paradox inherent in content-analysing privacy systems. This positions the proposed system as a practical, immediately deployable middle ground between passive OS-level permission indicators and expensive professional counter-surveillance equipment. Keywords: acoustic privacy, ultrasonic jamming, voice assistant privacy, covert device detection, zero-trust sensing, microphone obstruction