Sonicumos: An Enhanced Active Face Liveness Detection System via Ultrasonic and Video Signals

Abstract

Sonicumos is an enhanced behavior-based face liveness detection system that combines ultrasonic and video signals to sense the 3D head gestures. As face authentication becomes increasingly prevalent, the need for a reliable liveness detection system is paramount. Traditional behavior-based liveness detection methods (e.g., eye-blinking, nodding, etc.), which are widely deployed in mission-critical scenarios like finance and banking applications today, are prone to advanced media-based facial forgery attacks. Sonicumos aims to incorporate the traditional behavior-based method for active liveness detection without introducing extra user burden. By employing ultrasonic signals, Sonicumos capitalizes on the head gestures, significantly raising the security bar. Our approach utilizes the frequency-modulated continuous-wave (FMCW) ultrasonic radar for robust 3D gesture recognition compatible with face authentication. We also propose a new dual-feature fusion network that integrates audio and video features at the feature level to increase detection accuracy and resilience against numerous attacks. Our prototype has been tested on seven off-the-shelf Android/iOS smartphones, achieving an overall detection accuracy of 95.83% at an equal error rate (EER) of 4.96% when dealing with 3D impersonation attacks.