用空调传感器偷听人说话,还能还原清晰语音。
WaLi: Can Pressure Sensors in HVAC Systems Capture Human Speech?
- 用复数域变换网络捕捉语音细微特征,从低采样数据重建语音。
- 在0.5kHz采样下实现1.24的基频失真度,语音可懂度达1.78分。
- 揭示空调传感器隐私风险,适合安全与隐私研究者关注。
压力传感器是现代暖通空调(HVAC)系统的组成部分。由于其工作范围为0-10帕,支持0.5-2千赫兹的高采样频率,且常靠近人体,因此可被用于窃听机密语音——因为人类语音同样处于0-10帕的声压范围,且可懂语音带宽达4千赫兹。本文提出WaLi,通过以下技术贡献,从低分辨率、噪声干扰的压力传感器数据中重构出可理解的语音:(i) WaLi可在最低0.5千赫兹采样频率下重建可懂语音,而此前方法仅能检测热词/短语;其采用复数域变换器与复数全局注意力块(CGAB),捕捉低分辨率数据中的音素间与音素内依赖关系。(ii) WaLi通过重建缺失频率的干净幅度与相位,有效抑制暖通系统风扇与管道振动引入的瞬态噪声。我们在两家匿名工业设施的实际暖通系统上评估该攻击。实测结果表明,对0.5至8千赫兹的上采样,基频失真度(LSD)为1.24,语音质量感知评分(NISQA-MOS)达1.78。我们认为,此精度水平带来的隐私威胁此前未被关注。同时,我们也提供了防御方案。
原文摘要 · Abstract (English)
Pressure sensors are an integrated component of modern Heating, Ventilation, and Air Conditioning (HVAC) systems. As these pressure sensors operate within the 0-10 Pa range, support high sampling frequencies of 0.5-2 kHz, and are often placed close to human proximity, they can be used to eavesdrop on confidential speech, since human speech has a similar audible range of 0-10 Pa and a bandwidth of 4 kHz for intelligible quality. This paper presents WaLi, which reconstructs intelligible speech from the low-resolution and noisy pressure sensor data with the following technical contributions: (i) WaLi reconstructs intelligible speech from a minimum of 0.5 kHz sampling frequency of pressure sensors, whereas previous work can only detect hot words/phrases. WaLi uses a complex-valued conformer and Complex Global Attention Block (CGAB) to capture inter-phoneme and intra-phoneme dependencies that exist in the low-resolution pressure sensor data. (ii) WaLi handles the transient noise injected from HVAC fans and duct vibrations by reconstructing both the clean magnitude and phase of the missing frequencies of the low-frequency aliased components. We evaluate our attack on practical HVAC systems located in two anonymous industrial facilities. Extensive studies on real-world pressure sensors show an LSD of 1.24 and an NISQA-MOS of 1.78 for 0.5 kHz to 8 kHz upsampling. We believe that such levels of accuracy pose a significant threat when viewed from a privacy perspective that has not been addressed before for pressure sensors. We also provide defenses for the attack.
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