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

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 behaviorbased 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 continuouswave (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

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Publication Details

Journal
IEEE Transactions on Mobile Computing
Published
2025-04-29
DOI
https://doi.org/10.1109/tmc.2025.3565689
Citations
1
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
1.28
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Sonicumos: An Enhanced Active Face Liveness Detection System via Ultrasonic and Video Signals

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article

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

Qian Wang, Lingchen Zhao, Peipei Jiang, Jianhao Cheng, Cong Wang, Chao Shen, Yihao Wu
article en
1 citations

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 behaviorbased 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 continuouswave (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

IEEE Transactions on Mobile ComputingVol. 24(10)
City University of Hong Kong (HK), Wuhan University (CN), Xi'an Jiaotong University (CN)
Climate action
Openalex Percentile: Top 21%
Face recognition and analysis
1.28
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