FaceRevelio: a face liveness detection system for smartphones with a single front camera

Facial authentication mechanisms are gaining traction on smartphones because of their convenience and increasingly good performance of face recognition systems. However, mainstream systems use traditional 2D face recognition technologies, which are vulnerable to various spoofing attacks. Existing systems perform liveness detection via specialized hardware, such as infrared dot projectors and dedicated cameras. Although effective, such methods do not align well with the smartphone industry's desire to maximize screen space. This paper presents a new liveness detection system, FaceRevelio, for commodity smartphones with a single front camera. It utilizes the smartphone screen to illuminate a user's face from multiple directions. The facial images captured under varying illumination enable the recovery of the face surface normals via photometric stereo, which can then be integrated into a 3D shape. We leverage the facial depth features of this 3D surface to distinguish a human face from its 2D counterpart. On top of this, we change the screen via a light passcode consisting of a combination of random light patterns to provide security against replay attacks. We evaluate FaceRevelio with 30 users trying to authenticate under various lighting conditions and with a series of 2D spoofing attacks. The results show that using a passcode of 1s, FaceRevelio achieves a mean EER of 1.4% and 0.15% against photo and video attacks, respectively.

[1]  Max K. Agoston Computer Graphics And Geometric Modelling: Implementation & Algorithms , 2005 .

[2]  King-Sun Fu,et al.  IEEE Transactions on Pattern Analysis and Machine Intelligence Publication Information , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

[4]  Bing Zhou,et al.  EchoPrint: Two-factor Authentication using Acoustics and Vision on Smartphones , 2018, MobiCom.

[5]  Jang-Hee Yoo,et al.  Liveness Detection for Embedded Face Recognition System , 2008 .

[6]  Di Tang,et al.  Face Flashing: a Secure Liveness Detection Protocol based on Light Reflections , 2018, NDSS.

[7]  Lin Sun,et al.  Monocular camera-based face liveness detection by combining eyeblink and scene context , 2011, Telecommun. Syst..

[8]  Gregory R. Koch,et al.  Siamese Neural Networks for One-Shot Image Recognition , 2015 .

[9]  Robert H. Deng,et al.  A Closer Look Tells More: A Facial Distortion Based Liveness Detection for Face Authentication , 2019, AsiaCCS.

[10]  Tao Li,et al.  Your face your heart: Secure mobile face authentication with photoplethysmograms , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[11]  Parham Aarabi,et al.  Adversarial Attacks on Face Detectors Using Neural Net Based Constrained Optimization , 2018, 2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP).

[12]  Robert J. Woodham,et al.  Photometric method for determining surface orientation from multiple images , 1980 .

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

[14]  L. Trefethen,et al.  Numerical linear algebra , 1997 .

[15]  Richa Singh,et al.  Disguise detection and face recognition in visible and thermal spectrums , 2013, 2013 International Conference on Biometrics (ICB).

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

[17]  Wonjun Kim,et al.  Face Liveness Detection From a Single Image via Diffusion Speed Model , 2015, IEEE Transactions on Image Processing.

[18]  Guoying Zhao,et al.  Face Liveness Detection by rPPG Features and Contextual Patch-Based CNN , 2019, ICBEA.

[19]  Hideki Hayakawa Photometric stereo under a light source with arbitrary motion , 1994 .

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

[21]  Philipp Birken,et al.  Numerical Linear Algebra , 2011, Encyclopedia of Parallel Computing.

[22]  Rob Sumner Processing RAW Images in MATLAB , 2014 .

[23]  Edward H. Adelson,et al.  A multiresolution spline with application to image mosaics , 1983, TOGS.

[24]  Qian Zhang,et al.  EchoFace: Acoustic Sensor-Based Media Attack Detection for Face Authentication , 2020, IEEE Internet of Things Journal.

[25]  Jean-Denis Durou,et al.  Variational Methods for Normal Integration , 2017, Journal of Mathematical Imaging and Vision.

[26]  A. Viterbi CDMA: Principles of Spread Spectrum Communication , 1995 .

[27]  Qing Song,et al.  Attacks on state-of-the-art face recognition using attentional adversarial attack generative network , 2018, Multim. Tools Appl..

[28]  Anthony Rowe,et al.  Indoor pseudo-ranging of mobile devices using ultrasonic chirps , 2012, SenSys '12.

[29]  Josef Bigün,et al.  Real-Time Face Detection and Motion Analysis With Application in “Liveness” Assessment , 2007, IEEE Transactions on Information Forensics and Security.

[30]  Tian-Tsong Ng,et al.  Recaptured photo detection using specularity distribution , 2008, 2008 15th IEEE International Conference on Image Processing.

[31]  Marinella Cadoni,et al.  Liveness detection based on 3D face shape analysis , 2013, 2013 International Workshop on Biometrics and Forensics (IWBF).

[32]  R. Jenny,et al.  Fundamentals of Optics , 2001 .

[33]  Anil K. Jain,et al.  Secure Face Unlock: Spoof Detection on Smartphones , 2016, IEEE Transactions on Information Forensics and Security.

[34]  Max K. Agoston,et al.  Computer graphics and geometric modelling - implementation and algorithms , 2005 .

[35]  Pietro Perona,et al.  One-shot learning of object categories , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[36]  Donald J. Berndt,et al.  Using Dynamic Time Warping to Find Patterns in Time Series , 1994, KDD Workshop.

[37]  Kimberly A. Dukes Gram–Schmidt Process† , 2014 .