Your face your heart: Secure mobile face authentication with photoplethysmograms

Face authentication emerges as a powerful method for preventing unauthorized access to mobile devices. It is, however, vulnerable to photo-based forgery attacks (PFA) and videobased forgery attacks (VFA), in which the adversary exploits a photo or video containing the user's frontal face. Effective defenses against PFA and VFA often rely on liveness detection, which seeks to find a live indicator that the submitted face photo or video of the legitimate user is indeed captured in real time. In this paper, we propose FaceHeart, a novel and practical face authentication system for mobile devices. FaceHeart simultaneously takes a face video with the front camera and a fingertip video with the rear camera on COTS mobile devices. It then achieves liveness detection by comparing the two photoplethysmograms independently extracted from the face and fingertip videos, which should be highly consistent if the two videos are for the same live person and taken at the same time. As photoplethysmograms are closely tied to human cardiac activity and almost impossible to forge or control, FaceHeart is strongly resilient to PFA and VFA. Extensive user experiments on Samsung Galaxy S5 have confirmed the high efficacy and efficiency of FaceHeart.

[1]  Alex X. Liu,et al.  Secure unlocking of mobile touch screen devices by simple gestures: you can see it but you can not do it , 2013, MobiCom.

[2]  Prasant Mohapatra,et al.  Sensor-assisted facial recognition: an enhanced biometric authentication system for smartphones , 2014, MobiSys.

[3]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[4]  Tao Li,et al.  iLock: Immediate and Automatic Locking of Mobile Devices against Data Theft , 2016, CCS.

[5]  Ashok Veeraraghavan,et al.  DistancePPG: Robust non-contact vital signs monitoring using a camera , 2015, Biomedical optics express.

[6]  Martina Mueller,et al.  Development and Validation of a Smartphone Heart Rate Acquisition Application for Health Promotion and Wellness Telehealth Applications , 2012, International journal of telemedicine and applications.

[7]  Robert H. Deng,et al.  Seeing Your Face Is Not Enough: An Inertial Sensor-Based Liveness Detection for Face Authentication , 2015, CCS.

[8]  Rui Zhang,et al.  TouchIn: Sightless two-factor authentication on multi-touch mobile devices , 2014, 2014 IEEE Conference on Communications and Network Security.

[9]  Tomasz Kocejko,et al.  Proceedings of the Federated Conference on Computer Science and Information Systems pp. 405–410 ISBN 978-83-60810-22-4 Measuring Pulse Rate with a Webcam – a Non-contact Method for Evaluating Cardiac Activity , 2022 .

[10]  Matti Pietikäinen,et al.  Remote Heart Rate Measurement from Face Videos under Realistic Situations , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Stefanos Zafeiriou,et al.  Incremental Face Alignment in the Wild , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Josef Bigün,et al.  Non-intrusive liveness detection by face images , 2009, Image Vis. Comput..

[13]  L. O. Svaasand,et al.  Remote plethysmographic imaging using ambient light. , 2008, Optics express.

[14]  Shuchang Xu,et al.  Robust efficient estimation of heart rate pulse from video. , 2014, Biomedical optics express.

[15]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[16]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[17]  Bernard Widrow,et al.  Least-mean-square adaptive filters , 2003 .

[18]  Matti Pietikäinen,et al.  Face spoofing detection from single images using micro-texture analysis , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[19]  Yoshinori Kuno,et al.  Robust Heart Rate Measurement from Video Using Select Random Patches , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[20]  Rui Zhang,et al.  Your song your way: Rhythm-based two-factor authentication for multi-touch mobile devices , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[21]  Bernard Widrow,et al.  Least-Mean-Square Adaptive Filters: Haykin/Least-Mean-Square Adaptive Filters , 2005 .

[22]  Naser Damer,et al.  2D face liveness detection: An overview , 2012, 2012 BIOSIG - Proceedings of the International Conference of Biometrics Special Interest Group (BIOSIG).

[23]  Nir Friedman,et al.  Bayesian Network Classifiers , 1997, Machine Learning.

[24]  Guoliang Xue,et al.  Unobservable Re-authentication for Smartphones , 2013, NDSS.

[25]  Yi Li,et al.  Face Liveness Detection from a Single Image with Sparse Low Rank Bilinear Discriminative Model , 2010, ECCV.

[26]  Xavier Maldague,et al.  Infrared face recognition: A literature review , 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

[27]  Ian H. Witten,et al.  The WEKA data mining software: an update , 2009, SKDD.

[28]  Radford M. Neal Pattern Recognition and Machine Learning , 2007, Technometrics.

[29]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[30]  Rosalind W. Picard,et al.  Non-contact, automated cardiac pulse measurements using video imaging and blind source separation , 2022 .