ToothSonic: Earable Authentication via Acoustic Toothprint

Zi Wang, Yili Ren, Yingying Chen, Jie Yang

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Earables (ear wearables) are rapidly emerging as a new platform encompassing a diverse range of personal applications. The traditional authentication methods hence become less applicable and inconvenient for earables due to their limited input interface. Nevertheless, earables often feature rich around-The-head sensing capability that can be leveraged to capture new types of biometrics. In this work, we propose ToothSonic that leverages the toothprint-induced sonic effect produced by a user performing teeth gestures for earable authentication. In particular, we design representative teeth 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 ToothSonic 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 ToothSonic achieves up to 95% accuracy with only one of the users' tooth gestures.

Original languageEnglish (US)
Article number78
JournalProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Volume6
Issue number2
DOIs
StatePublished - Jul 2022
Externally publishedYes

Keywords

  • Acoustic Sensing
  • Biometrics
  • Ear Canal
  • Earable Authentication
  • Tooth
  • Wearable

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'ToothSonic: Earable Authentication via Acoustic Toothprint'. Together they form a unique fingerprint.

Cite this