An Eavesdropping System Based on Magnetic Side-Channel Signals Leaked by Speakers

IF 3.9 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS ACM Transactions on Sensor Networks Pub Date : 2023-12-11 DOI:10.1145/3637063
Qianru Liao, Yongzhi Huang, Yandao Huang, Kaishun Wu
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Abstract

The use of speakers in electronic devices has become widespread, but the security risks associated with micro-speakers, such as earphones, are often overlooked. Many assume that soundproof barriers can prevent sound leakage and protect privacy. This paper presents the prototype MagEar, an eavesdropping system that exploits magnetic side-channel signals leaked by a micro-speaker to restore intelligible human speech. MagEar outperforms some high-precision magnetometers in detecting magnetic fields at the nanotesla level. Even at a distance of 60 cm, it can recover high-quality audio with a 90% similarity to the original audio. Moreover, the MagEar prototype is portable and can be concealed within a headset housing. We have implemented MagEar as a proof-of-concept system and conducted multiple case studies on the eavesdropping of various speaker-embedded devices, including earphones. The recovered speech can be transcribed using automatic speech recognition techniques, even when obstructed by soundproof walls. It is our aspiration that our work can prompt manufacturers to reconsider the security vulnerabilities of speakers.

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基于扬声器泄露的磁性侧信道信号的窃听系统
扬声器在电子设备中的使用已经非常普遍,但与耳机等微型扬声器相关的安全风险却常常被忽视。许多人认为隔音屏障可以防止声音泄漏并保护隐私。本文介绍的 MagEar 原型是一种窃听系统,它利用微型扬声器泄露的磁性侧信道信号来还原可理解的人类语音。MagEar 在探测纳特斯拉级磁场方面的表现优于一些高精度磁力计。即使在 60 厘米的距离内,它也能恢复与原始音频相似度高达 90% 的高质量音频。此外,MagEar 原型机便于携带,可以隐藏在耳机外壳中。我们已将 MagEar 作为概念验证系统实施,并对包括耳机在内的各种扬声器嵌入式设备的窃听情况进行了多次案例研究。即使在隔音墙阻挡的情况下,也能使用自动语音识别技术转录恢复的语音。我们希望我们的工作能促使制造商重新考虑扬声器的安全漏洞。
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来源期刊
ACM Transactions on Sensor Networks
ACM Transactions on Sensor Networks 工程技术-电信学
CiteScore
5.90
自引率
7.30%
发文量
131
审稿时长
6 months
期刊介绍: ACM Transactions on Sensor Networks (TOSN) is a central publication by the ACM in the interdisciplinary area of sensor networks spanning a broad discipline from signal processing, networking and protocols, embedded systems, information management, to distributed algorithms. It covers research contributions that introduce new concepts, techniques, analyses, or architectures, as well as applied contributions that report on development of new tools and systems or experiences and experiments with high-impact, innovative applications. The Transactions places special attention on contributions to systemic approaches to sensor networks as well as fundamental contributions.
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