BreathSign: Transparent and Continuous In-ear Authentication Using Bone-conducted Breathing Biometrics

As one of the most natural physiological activities, breathing provides an effective and ubiquitous approach for continuous authentication. Inspired by that, this paper presents BreathSign, which reveals a novel biometric characteristic using bone-conducted human breathing sound and provides an anti-spoofing and transparent authentication mechanism based on inward-facing microphones on commercial earphones. To explore the breathing differences among persons, we first analyze how the breathing sound propagates in the body, and then derive unique body physics-level features from breathing-induced body sounds. Furthermore, to eliminate the impact of behavioral biometrics, we design a triple network model to reconstruct breathing behavior-independent features. Extensive experiments with 20 subjects over a period have been conducted to evaluate the accuracy, robustness, and vulnerability of BreathSign. The results show that our system accurately authenticates users with an average authentication accuracy rate of 95.17% via only one breathing cycle, and effectively defends against various spoofing attacks with an average spoofing attack detection rate of 98.25%. Compared with other continuous authentication solutions, BreathSign extracts hard-to-forge biometrics in the effortless human breathing activity for authentication and can be easily implemented on commercial earphones with high usability and enhanced security.