SuperEar: Eavesdropping on Mobile Voice Calls via Stealthy Acoustic Metamaterials
Zhiyuan Ning, Zhanyong Tang, Juan He, Weizhi Meng, Yuntian Chen, Jie Zhang, Zheng Wang
Abstract
Acoustic eavesdropping is a privacy risk, but existing attacks rarely work in real outdoor situations where people make phone calls on the move. We present SuperEar, the first portable system that uses acoustic metamaterials to reliably capture conversations in these scenarios. We show that the threat is real as a practical prototype can be implemented to enhance faint signals, cover the full range of speech with a compact design, and reduce noise and distortion to produce clear audio. We show that SuperEar can be implemented from low-cost 3D-printed parts and off-the-shelf hardware. Experimental results show that SuperEar can recover phone call audio with a success rate of over 80% at distances of up to 4.6 m -more than twice the range of previous approaches. Our findings highlight a new class of privacy threats enabled by metamaterial technology that requires attention. CCS Concepts • Security and privacy → Usability in security and privacy.
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