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Speechless: Analyzing the Threat to Speech Privacy from Smartphone Motion Sensors

机译:无语:分析来自智能手机运动传感器的语音隐私威胁

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According to recent research, motion sensors available on current smartphone platforms may be sensitive to speech signals. From a security and privacy perspective, this raises a serious concern regarding sensitive speech reconstruction, and speaker or gender identification by a malicious application having unrestricted access to motion sensor readings, without using the microphone. In this paper, we revisit this important line of research and closely inspect the effect of speech on smartphone motion sensors, in particular, gyroscope and accelerometer. First, we revisit the previously studied scenario (Michalevsky et al.; USENIX Security 2014), where the smartphone shares a common surface with a loudspeaker (with subwoofer) generating speech signals. We observe some effect on the motion sensor signals, which may indeed allow speaker and gender recognition to an extent. However, we also argue that the recorded effect on the sensor readings is possibly from conductive vibrations through the shared surface instead of direct acoustic vibrations due to speech as perceived in previous work. Second, we further extend the previous work by analyzing the effect of speech produced by (1) other less powerful speakers like the in-built laptop and smartphone speakers, and (2) live humans. Our experiments show that in-built laptop speakers were only able to affect the accelerometer when the laptop and the motion sensor shared a surface. Smartphone speakers were not found to be powerful enough to invoke a response in the motion sensors through aerial vibrations. We also report that in the presence of live human speech, we did not notice any effect on the motion sensor readings. Our results have two-fold implications. First, human-rendered speech seems potentially incapacitated to trigger smartphone motion sensors within the limited sampling rates imposed by the smartphone operating systems. Second, it seems that even machine-rendered speech may not be powerful enough to affect smartphone motion sensors through the aerial medium, although it may induce vibrations through a conductive surface that these sensors, especially accelerometer, could pick up if a relatively powerful speaker is used. Overall, our results suggest that smartphone motion sensors may pose a threat to speech privacy only in some limited scenarios.
机译:根据最近的研究,当前智能手​​机平台上可用的运动传感器可能对语音信号敏感。从安全和隐私角度来看,这对敏感性语音重建和扬声器或性别识别具有不受限制的运动传感器读数的恶意应用来提出严重关切,而不使用麦克风。在本文中,我们重新审视了这一重要的研究线,并密切检查了智能手机运动传感器的效果,特别是陀螺仪和加速度计。首先,我们重新审视前研究的场景(Michalevsky等; Usenix Security 2014),智能手机与扬声器(带有低音炮)产生的共同面,产生语音信号。我们观察到运动传感器信号的一些影响,这可能确实允许扬声器和性别识别程度。然而,我们还认为对传感器读数的记录效果可能来自通过共用表面的导电振动而不是由于先前的工作中所感知的语音而导致的直接声学振动。其次,我们进一步通过分析(1)其他强大的扬声器(如In-USICE的笔记本电脑和智能手机扬声器)产生的语音的效果来扩展以前的工作,(2)活人类。我们的实验表明,在笔记本电脑和运动传感器共用时,内置的笔记本电脑扬声器只能影响加速度计。智能手机扬声器未能通过空中振动来调用运动传感器中的响应。我们还报告说,在现场言论的存在下,我们没有注意到对运动传感器读数的任何影响。我们的结果有两倍的影响。首先,人为渲染的语音似乎可能无法突触,以触发智能手机操作系统强加的有限采样率内的智能手机运动传感器。其次,似乎甚至机器呈现的语音可能不足以通过空中介质影响智能手机运动传感器,尽管它可能会引起这些传感器,尤其是加速度计的导电表面,如果相对强大的扬声器可以接收用过的。总体而言,我们的结果表明,智能手机运动传感器可能在一些有限的情况下才能对语音隐私构成威胁。

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