연구 분야: Analysis
학회: SENSYS '24: Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems
With the advancement of AI-powered personal voice assistants, speaker authentication via earbuds has become increasingly vital, serving as a critical interface between users and mobile devices. However, existing audio-based speaker authentication methods fail to defend against voice spoofing threats such as replay and deep-fake attacks. To counteract these risks, we introduce PiezoBud, a pioneering multi-modal user authentication system that is truly practical and lightweight for earbuds. PiezoBud uses miniature piezoelectric sensors to detect micro-vibrations on the skin, extracting user-specific biometric data to authenticate legitimate access on the local smartphone and protect against malicious attacks. Our exploratory study, involving 85 participants, demonstrates the effectiveness of PiezoBud in various everyday scenarios, including ambient noise, body movement, and in-ear media playing. Using only 15 seconds of enrollment data, PiezoBud achieves an Equal Error Rate (EER) of 1.05% and attain a mean authentication latency of 0.06 seconds on mobile devices. We also evaluate PiezoBud's effectiveness in countering challenging adaptive attack scenarios and its overall performance in various real-world situations. Our evaluation highlights that PiezoBud stands out as a practical, resilient, responsive, and secure option for earbuds users.
| 발행 연도 | 2024년 |
|---|---|
| 인용수 | 0 |
| 출판 국가 | United States, Austria |
| 사이트 | ACM |
| 좋아요 수 | 0 |