Phoneme-Based Proactive Anti-Eavesdropping with Controlled Recording Privilege
CoRR(2024)
摘要
The widespread smart devices raise people's concerns of being eavesdropped
on. To enhance voice privacy, recent studies exploit the nonlinearity in
microphone to jam audio recorders with inaudible ultrasound. However, existing
solutions solely rely on energetic masking. Their simple-form noise leads to
several problems, such as high energy requirements and being easily removed by
speech enhancement techniques. Besides, most of these solutions do not support
authorized recording, which restricts their usage scenarios. In this paper, we
design an efficient yet robust system that can jam microphones while preserving
authorized recording. Specifically, we propose a novel phoneme-based noise with
the idea of informational masking, which can distract both machines and humans
and is resistant to denoising techniques. Besides, we optimize the noise
transmission strategy for broader coverage and implement a hardware prototype
of our system. Experimental results show that our system can reduce the
recognition accuracy of recordings to below 50% under all tested speech
recognition systems, which is much better than existing solutions.
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