Ning, Z., Wang, Z. orcid.org/0000-0001-6157-0662 and Tang, Z. (2025) MetaGuardian: Enhancing Voice Assistant Security through Advanced Acoustic Metamaterials. In: ACM MOBICOM '25: Proceedings of the 31st Annual International Conference on Mobile Computing and Networking. ACM MOBICOM '25: 31st Annual International Conference on Mobile Computing and Networking, 04-08 Nov 2025, Hong Kong, China. . ACM, pp. 788-801. ISBN: 979-8-4007-1129-9.
Abstract
Voice assistants (VAs) have become integral to daily life, yet their always-on microphones make them attractive targets for attacks that threaten user privacy and safety. We present MetaGuardian, the first system to leverage acoustic metamaterials to defend against three major classes of attacks for VAs - inaudible, adversarial, and laser-based - within a single, portable design. Unlike prior defenses, MetaGuardian can be seamlessly integrated into the enclosures of commercial smart devices, providing strong protection without requiring software modification, hardware redesign, or costly machine learning models. MetaGuardian leverages mutual impedance effects between metamaterial units to extend the protection range to 16–40 kHz, effectively blocking wideband inaudible attacks. It also employs a carefully designed coiled space structure to disrupt adversarial signals while preserving normal VA operations. Its universal design allows flexible adaptation to different devices, striking a balance between portability and protection effectiveness. In controlled evaluations, MetaGuardian achieves a high defense success rate across all attack types, offering a practical and reliable foundation for securing VAs on smart devices.
Metadata
| Item Type: | Proceedings Paper |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | This is an author produced version of a conference paper published in ACM MOBICOM '25: Proceedings of the 31st Annual International Conference on Mobile Computing and Networking, made available under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
| Date Deposited: | 12 Sep 2025 11:22 |
| Last Modified: | 21 Apr 2026 19:56 |
| Status: | Published |
| Publisher: | ACM |
| Identification Number: | 10.1145/3680207.3765246 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:231426 |
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