User Authentication on Smart Speakers Leveraging Acoustic Imaging

The user authentication has drawn increasingly attention as the smart speaker becomes more prevalent. For example, smart speakers that can verify who is sending voice commands can mitigate various types of attacks, such as replay attack or impersonation attack. Existing user authentication solutions either cannot be applicable to smart speakers directly or require certain additional user-device interaction or pre-installed infrastructure, which may severely affect the user experience and create extra burdens to users. In this work, we propose a user authentication system utilizing acoustic images, which are derived from the smart speaker by emitting beep signals and sensing echoes from the user’s body with its microphone array, as the proof for user authentication. Given the acoustic samplings of the reflected beep signal, our system designs a distance estimation component by applying a correlation based technique on the beamformed signal to estimate the distance between the user and microphone array. Our image construction component then constructs a virtual imaging plane using the estimated distance and steers the array towards each grid of the plane to generate an acoustic image of the user. We also propose a transfer learning-based method to derive efficient features from the constructed images, and employ SVM classifiers for accurate user authentication. Moreover, to ensure the accuracy of our system, our user direction estimation scheme could further estimate the DoA of the user’s voice command to make sure that the user stands in front of the smart speaker during the authentication process. Our extensive experiments demonstrate that our system is robust and accurate across various scenarios.