Voice assistants are popular to wearable devices with limited input and output capabilities, however vulnerable to voice attacks, which cheat a voice assistant by playing forged voice commands without user awareness. In this paper, we propose VOGUE, which captures unique yet stable pattern of speech movement sequences of speakers with embedded gyroscope in wearable devices, to distinguish between registered legal user and malicious attackers (human or machines). The design of VOGUE is based on two key observations. First, speech, as a type of highly complex motor task, inherently requires coordinated actions of many orofacial, laryngeal, pharyngeal, and respiratory muscles, and the collective movements of muscles propagate to distant body segments. Second, to generate a certain word, the speech movement sequence of a speaker is known to be distinctive, and can be captured by inertial sensors. We implement VOGUE on three kinds of COTS android devices including smart glasses, watches and phones, and conduct comprehensive evaluation on the performances. Experimental results show that VOGUE achieves a mean false-acceptance rate (FAR) and false- rejection rate (FRR) of 2.23% and 2.48%, respectively, even under sophisticated voice impersonation attacks.

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