Guoming Zhang (Zhejiang University), Xiaoyu Ji (Zhejiang University), Xinfeng Li (Zhejiang University), Gang Qu (University of Maryland), Wenyuan Xu (Zhejing University)

DolphinAttacks (i.e., inaudible voice commands) modulate audible voices over ultrasounds to inject malicious commands silently into voice assistants and manipulate controlled systems (e.g., doors or smart speakers). Eliminating DolphinAttacks is challenging if ever possible since it requires to modify the microphone hardware. In this paper, we design EarArray, a lightweight method that can not only detect such attacks but also identify the direction of attackers without requiring any extra hardware or hardware modification. Essentially, inaudible voice commands are modulated on ultrasounds that inherently attenuate faster than the one of audible sounds. By inspecting the command sound signals via the built-in multiple microphones on smart devices, EarArray is able to estimate the attenuation rate and thus detect the attacks. We propose a model of the propagation of audible sounds and ultrasounds from the sound source to a voice assistant, e.g., a smart speaker, and illustrate the underlying principle and its feasibility. We implemented EarArray using two specially-designed microphone arrays and our experiments show that EarArray can detect inaudible voice commands with an accuracy of 99% and recognize the direction of the attackers with an accuracy of 97.89%.

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Shangqi Lai (Monash University), Xingliang Yuan (Monash University), Joseph K. Liu (Monash University), Xun Yi (RMIT University), Qi Li (Tsinghua University), Dongxi Liu (Data61, CSIRO), Surya Nepal (Data61, CSIRO)

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Zhuoran Liu (Radboud university), Niels Samwel (Radboud University), Léo Weissbart (Radboud University), Zhengyu Zhao (Radboud University), Dirk Lauret (Radboud University), Lejla Batina (Radboud University), Martha Larson (Radboud University)

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Guoming Zhang, Xiaoyu Ji (Zhejiang University)

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Zeyu Lei (Purdue University), Yuhong Nan (Purdue University), Yanick Fratantonio (Eurecom & Cisco Talos), Antonio Bianchi (Purdue University)

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