加速度计
计算机科学
陀螺仪
窃听
许可
惯性测量装置
可扩展性
计量单位
实时计算
计算机安全
人工智能
数据库
工程类
物理
航空航天工程
操作系统
法学
量子力学
政治学
作者
Ming Gao,Yajie Liu,Yike Chen,Yimin Li,Zhongjie Ba,Xian Xu,Jinsong Han,Kui Ren
标识
DOI:10.1109/tdsc.2022.3193130
摘要
Eavesdropping via inertial measurement units (IMUs) has brought growing concerns over smartphone users' privacy. In such attacks, adversaries utilize IMUs, including accelerometers and gyroscopes, which require zero permissions for access to acquire speeches. A common countermeasure is to limit sampling rates (within 200 Hz) to reduce overlap of vocal fundamental bands (85 $\sim$ 255 Hz) and inertial measurements (0 $\sim$ 100 Hz). Nevertheless, we observe that IMUs sampling below 200 Hz still record adequate speech-related information because of aliasing distortions. Accordingly, we propose a practical side-channel attack, namely InertiEAR , to break the defense of sampling rate restriction on the zero-permission eavesdropping. It leverages accelerometers and gyroscopes jointly to eavesdrop on both top and bottom speakers in smartphones. We exploit coherence between responses of the built-in accelerometer and gyroscope using a mathematical model. The coherence allows precise segmentation without manual assistance. We also mitigate the impact of hardware diversity and achieve better device-independent performance than existing approaches that have to massively increase training data from different smartphones for a scalable network model. These two advantages re-enable zero-permission attacks but also extend the attacking surface and endangering degree to off-the-shelf smartphones. InertiEAR achieves the recognition accuracy of 78.8% with the cross-device accuracy of up to 60.9% among 12 smartphones.
科研通智能强力驱动
Strongly Powered by AbleSci AI