Poster: Fingerprint-Face Friction Based Earable Authentication

Abstract

Ear wearables (earables) have become an emerging and wide acceptable platform for various applications. Because of the limited input interface of earables, traditional authentication methods become less desired. However, the feature-rich sensing abilities of earables and the unique human face-ear channel bring us new sensing opportunities to reutilize fingerprints. In this work, we proposed SlidePass, a secure earables authentication system that leverages the finger-face acoustic friction produced by sliding finger gestures on the face. In particular, our system leverages the inward-facing microphone of the earables to reliably capture the acoustic of finger-face frictions. The core insight of our system is to utilize the face as a natural scanner for finger-face friction and earables to capture and reconstruct the fingerprint features. SlidePass is specially designed for earables. Due to the finger-face friction captured and encrypted by the face channel that is unique and hidden in the human skull, SlidePass is more resistant to various spoofing attacks. Our preliminary evaluation included ten different fingerprints showing that SlidePass achieves an average accuracy of 94%.