Privacy-Preserving Fuzzy Commitment for Biometrics via Layered Error-Correcting Codes

With the widespread development of biometrics, concerns about security and privacy are increasing. In biometrics, template protection technology aims to protect the confidentiality of biometric templates (i.e., enrolled biometric data) by certain conversion. The fuzzy commitment scheme gives a practical way to protect biometric templates using a conventional error-correcting code. The scheme has both concealing and binding of templates, but it has some privacy problems. Specifically, in case of successful matching, stored biometric templates can be revealed. To address such problems, we improve the scheme. Our improvement is to coat with two error-correcting codes. In particular, our scheme can conceal stored biometric templates even in successful matching. Our improved scheme requires just conventional error-correcting codes as in the original scheme, and hence it gives a practical solution for both template security and privacy of biometric templates.

[1]  Martin Wattenberg,et al.  A fuzzy commitment scheme , 1999, CCS '99.

[2]  John Daugman,et al.  The importance of being random: statistical principles of iris recognition , 2003, Pattern Recognit..

[3]  T. Moon.  Error Correction Coding: Mathematical Methods and Algorithms , 2005 .

[4]  J. Pandey,et al.  ENHANCE FUZZY COMMITMENT SCHEME: AN APPROACH FOR POST QUANTUM CRYPTOSYSTEM , 2009 .

[5]  Yevgeniy Dodis,et al.  Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data , 2004, EUROCRYPT.

[6]  Frans M. J. Willems,et al.  On Privacy in Secure Biometric Authentication Systems , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[7]  Andreas Uhl,et al.  Iris-Biometric Fuzzy Commitment Schemes under Image Compression , 2013, CIARP.

[8]  Nasir D. Memon,et al.  A secure biometric authentication scheme based on robust hashing , 2005, MM&Sec '05.

[9]  Anil K. Jain,et al.  Handbook of Fingerprint Recognition , 2005, Springer Professional Computing.

[10]  John Daugman,et al.  High Confidence Visual Recognition of Persons by a Test of Statistical Independence , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Pascal Paillier,et al.  Public-Key Cryptosystems Based on Composite Degree Residuosity Classes , 1999, EUROCRYPT.

[12]  Christophe Rosenberger,et al.  An Overview on Privacy Preserving Biometrics , 2011 .

[13]  Frans M. J. Willems,et al.  Information Leakage in Fuzzy Commitment Schemes , 2010, IEEE Transactions on Information Forensics and Security.

[14]  Andrew Beng Jin Teoh,et al.  Random Multispace Quantization as an Analytic Mechanism for BioHashing of Biometric and Random Identity Inputs , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Madhu Sudan,et al.  A Fuzzy Vault Scheme , 2006, Des. Codes Cryptogr..

[16]  Anil K. Jain,et al.  Biometric Template Security , 2008, EURASIP J. Adv. Signal Process..

[17]  Thuc Dinh Nguyen,et al.  Gait authentication on mobile phone using biometric cryptosystem and fuzzy commitment scheme , 2015, International Journal of Information Security.

[18]  Feng Hao,et al.  Combining Crypto with Biometrics Effectively , 2006, IEEE Transactions on Computers.

[19]  Anil K. Jain,et al.  Hardening Fingerprint Fuzzy Vault Using Password , 2007, ICB.

[20]  Robert J. McEliece,et al.  A public key cryptosystem based on algebraic coding theory , 1978 .

[21]  Eul Gyu Im,et al.  Malware analysis using visualized images and entropy graphs , 2014, International Journal of Information Security.

[22]  Andreas Uhl,et al.  Statistical attack against iris-biometric fuzzy commitment schemes , 2011, CVPR 2011 WORKSHOPS.

[23]  Christoph Busch,et al.  Privacy enhancing technology for a 3D-face recognition system , 2007, BIOSIG.

[24]  Mauro Barni,et al.  eSketch: a privacy-preserving fuzzy commitment scheme for authentication using encrypted biometrics , 2010, MM&Sec '10.

[25]  Richard E. Blahut.  Algebraic Codes on Lines, Planes, and Curves: An Engineering Approach , 2008 .