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Due to the open nature of voice input, voice assistant (VA) systems (e.g.,Google Home and Amazon Alexa) are under a high risk of sensitive informationleakage (e.g., personal schedules and shopping accounts). Though the existingVA systems may employ voice features to identify users, they are stillvulnerable to various acoustic attacks (e.g., impersonation, replay and hiddencommand attacks). In this work, we focus on the security issues of the emergingVA systems and aim to protect the users' highly sensitive information fromthese attacks. Towards this end, we propose a system, WearID, which uses anoff-the-shelf wearable device (e.g., a smartwatch or bracelet) as a securetoken to verify the user's voice commands to the VA system. In particular,WearID exploits the readily available motion sensors from most wearables todescribe the command sound in vibration domain and check the received commandsound across two domains (i.e., wearable's motion sensor vs. VA device'smicrophone) to ensure the sound is from the legitimate user.

WearID: Wearable-Assisted Low-Effort Authentication to Voice Assistants using Cross-Domain Speech Similarity