Poster: Extracting Speech from Subtle Room Object Vibrations Using Remote mmWave Sensing
Cong Shi, Tianfang Zhang, Zhaoyi Xu, Shuping Li, Donglin Gao, Changming Li, Athina P. Petropulu, Chung‐Tse Michael Wu, Yingying Jennifer Chen · 2023
Speech privacy leakage has long been a public concern. Existing non-microphone-based eavesdropping attacks rely on physical contact or line-of-sight between the sensor (e.g., a motion sensor or a radar) and the victim sound source. In this poster, we investigate a new form of attack that remotely elicits speech from minute surface vibrations upon common room objects (e.g., paper bags, plastic storage bin) via mmWave sensing. We design and implement a highresolution software-defined phased-MIMO radar that integrates transmit beamforming, virtual array, and receive beamforming. The proposed system enhances sensing directivity by focusing all the mmWave beams toward a target room object. We successfully demonstrate such an attack by developing a deep speech recognition scheme grounded on unsupervised domain adaptation. Without prior training on the victim's data, our attack can achieve a high success rate of over 90% in recognizing simple digits.