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Wang, Z. (2022). Towards Ubiquitous User Authentication and Sensing Based on the Ear Canal and Toothprint Biometrics Using Ear Wearables. Retrieved from https://purl.lib.fsu.edu/diginole/2022_Summer_Wang_fsu_0071E_17085
Biometric-based authentication is gaining increasing attention for wearables and mobile applications. Meanwhile, the growing adoption of sensors in wearables and mobiles also provides opportunities to capture novel biometrics. In this proposal, we leverage the cutting-edge wearables to sense novel human biometrics and utilize them for user authentication, i.e., ear canal deformation and toothprint acoustic. First, we use ear wearables to sense ear canal deformation, and further design an ear canal deformation-based user authentication using ear wearables. Our system provides continuous and passive user authentication and is transparent to users. It leverages ear canal deformation that combines the ear canal's unique static geometry and dynamic motions when the user is speaking for authentication. It utilizes an acoustic sensing approach to capture the ear canal deformation with the built-in microphone and speaker of the in-ear wearable. Specifically, it first emits well-designed inaudible beep signals and records the reflected signals from the ear canal. It then analyzes the reflected signals and extracts fine-grained acoustic features that correspond to the ear canal deformation for user authentication. Our extensive experimental evaluation shows that our system can achieve a recall of 97.38% and an F1 score of 96.84%. Results also show that our system works well in noisy environments with various daily activities. Moreover, we propose a system that leverages the toothprint-induced sonic effect produced by a user performing teeth gestures for earable authentication. In particular, we design representative tooth gestures that can produce effective sonic waves carrying the information of the toothprint. To reliably capture the acoustic toothprint, it leverages the occlusion effect of the ear canal and the inward-facing microphone of the earables. It then extracts multi-level acoustic features to reflect the intrinsic toothprint information for authentication. The key advantages of toothprint-based biometrics are that it is suitable for earables and is resistant to various spoofing attacks as the acoustic toothprint is captured via the user's private teeth-ear channel that modulates and encrypts the sonic waves. Our experiment studies with 25 participants show that our system could achieve up to 95% accuracy with only one of the users' tooth gestures.
A Dissertation submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy.
Bibliography Note
Includes bibliographical references.
Advisory Committee
Jie Yang, Professor Directing Dissertation; Washington Mio, University Representative; Zhi Wang, Committee Member; Shayok Chakraborty, Committee Member.
Publisher
Florida State University
Identifier
2022_Summer_Wang_fsu_0071E_17085
Wang, Z. (2022). Towards Ubiquitous User Authentication and Sensing Based on the Ear Canal and Toothprint Biometrics Using Ear Wearables. Retrieved from https://purl.lib.fsu.edu/diginole/2022_Summer_Wang_fsu_0071E_17085