VocalLock: Sensing Vocal Tract for Passphrase-Independent User Authentication Leveraging Acoustic Signals on Smartphones
Published in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2020
Recommended citation: Li Lu, Jiadi Yu, Yingying Chen, Yan Wang. "VocalLock: Sensing Vocal Tract for Passphrase-Independent User Authentication Leveraging Acoustic Signals on Smartphones." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). 4(2), pp. 51:1-51:24. Cancun, Mexico. 2020. doi: 10.1145/3397320.
Proceedings of ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies is the premier international journal in ubiquitous computing, which is previously the top ranked international conference ACM UbiComp. This paper was also presented in ACM UbiComp 2020. ACM UbiComp is a CCF-A conference.
Abstract: Recent years have witnessed the surge of biometric-based user authentication for mobile devices due to its promising security and convenience. As a natural and widely-existed behavior, human speaking has been exploited for user authentication. Existing voice-based user authentication explores the unique characteristics from either the voiceprint or mouth movements, which is vulnerable to replay attacks and mimic attacks. During speaking, the vocal tract, including the static shape and dynamic movements, also exhibits the individual uniqueness, and they are hardly eavesdropped and imitated by adversaries. Hence, our work aims to employ the individual uniqueness of vocal tract to realize user authentication on mobile devices. Moreover, most voice-based user authentications are passphrase-dependent, which significantly degrade the user experience. Thus, such user authentications are pressed to be implemented in a passphrase-independent manner while being able to resist various attacks. In this paper, we propose a user authentication system, VocalLock, which senses the whole vocal tract during speaking to identify different individuals in a passphrase-independent manner on smartphones leveraging acoustic signals.
Presentation Venue: Session 1A: Security, Privacy, and Acceptance at ACM UbiComp 2020 @ Virtual, Online in Sep. 14, 2020.