Anti-Spoofing Techniques in Face Recognition, an Ensemble Based Approach

In this article we describe the implementation of a reliable and innovative ensemble-based technique that can prevent face spoofing attacks. The presented software is part of a technology developed in partnership with IsItYou, an Israeli company, that attempts to replace passwords with a face-based authentication system. Since the main problem of biometric systems is represented by the spoof attacks, IsItYou came with a solution to this, developing a unique technology that can identify spoof attacks, and authenticate only authorized humans. Inspired from deep learning techniques where ensemble-based solutions improve machine learning results by uniting several models, a software ensemble that combines multiple anti-spoofing methods, covering a larger range of spoof attacks and increasing overall security was developed. The article also shows the performances results and implementation details. The experimental results signpost our solution can provide first-rate results compared to the state-of-the-art approaches.

[1]  K. Harshika Image Quality Assessment for Fake Biometric Detection : Application to Iris , Fingerprint , and Face Recognition , 2017 .

[2]  Ricardo L. de Queiroz,et al.  Face-Spoofing 2D-Detection Based on Moiré-Pattern Analysis , 2015, IEEE Transactions on Information Forensics and Security.

[3]  Rinu Anna Varghese Face Anti-spoofing methods , 2015 .

[4]  Lin Sun,et al.  Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[5]  Sébastien Marcel,et al.  Spoofing Attacks To 2D Face Recognition Systems With 3D Masks , 2013, ICB 2013.

[6]  Xiaoming Liu,et al.  Face De-Spoofing: Anti-Spoofing via Noise Modeling , 2018, ECCV.

[7]  Junjie Yan,et al.  A face antispoofing database with diverse attacks , 2012, 2012 5th IAPR International Conference on Biometrics (ICB).

[8]  Razvan D. Albu Face anti-spoofing based on Radon transform , 2015, 2015 13th International Conference on Engineering of Modern Electric Systems (EMES).

[9]  Anil K. Jain,et al.  Face Spoof Detection With Image Distortion Analysis , 2015, IEEE Transactions on Information Forensics and Security.

[10]  Richard M. Stern,et al.  Fast Computation of the Difference of Low-Pass Transform , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Samarth Bharadwaj,et al.  Computationally Efficient Face Spoofing Detection with Motion Magnification , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[12]  Matti Pietikäinen,et al.  Face liveness detection using dynamic texture , 2014, EURASIP J. Image Video Process..