Alignment-free cancelable iris biometric templates based on adaptive bloom filters

Biometric characteristics are largely immutable, i.e. unprotected storage of biometric data provokes serious privacy threats, e.g. identity theft, limited re-newability, or cross-matching. In accordance with the ISO/IEC 24745 standard, technologies of cancelable biometrics offer solutions to biometric information protection by obscuring biometric signal in a non-invertible manner, while biometric comparisons are still feasible in the transformed domain. In the presented work alignment-free cancelable iris biometrics based on adaptive Bloom filters are proposed. Bloom filter-based representations of binary biometric templates (iris-codes) enable an efficient alignment-invariant biometric comparison while a successive mapping of parts of a binary biometric template to a Bloom filter represents an irreversible transform. In experiments, which are carried out on the CASIA - v 3 iris database, it is demonstrated that the proposed system maintains biometric performance for diverse iris recognition algorithms, protecting biometric templates at high security levels.

[1]  Nalini K. Ratha,et al.  Cancelable iris biometric , 2008, 2008 19th International Conference on Pattern Recognition.

[2]  David Zhang,et al.  An analysis of BioHashing and its variants , 2006, Pattern Recognit..

[3]  Andrew Teoh Beng Jin,et al.  High security Iris verification system based on random secret integration , 2006 .

[4]  Nalini K. Ratha,et al.  Enhancing security and privacy in biometrics-based authentication systems , 2001, IBM Syst. J..

[5]  James K. Mullin,et al.  Optimal Semijoins for Distributed Database Systems , 1990, IEEE Trans. Software Eng..

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

[7]  Libor Masek,et al.  Recognition of Human Iris Patterns for Biometric Identification , 2003 .

[8]  Andrei Broder,et al.  Network Applications of Bloom Filters: A Survey , 2004, Internet Math..

[9]  Burton H. Bloom,et al.  Space/time trade-offs in hash coding with allowable errors , 1970, CACM.

[10]  Norimichi Tsumura,et al.  Tokenless Cancelable Biometrics Scheme for Protecting Iris Codes , 2010, 2010 20th International Conference on Pattern Recognition.

[11]  Rama Chellappa,et al.  Sectored Random Projections for Cancelable Iris Biometrics , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[12]  Patrick J. Flynn,et al.  Image understanding for iris biometrics: A survey , 2008, Comput. Vis. Image Underst..

[13]  Andreas Uhl,et al.  Weighted adaptive Hough and ellipsopolar transforms for real-time iris segmentation , 2012, 2012 5th IAPR International Conference on Biometrics (ICB).

[14]  T.E. Boult,et al.  Cracking Fuzzy Vaults and Biometric Encryption , 2007, 2007 Biometrics Symposium.

[15]  Andreas Uhl,et al.  Cancelable Iris Biometrics Using Block Re-mapping and Image Warping , 2009, ISC.

[16]  Andrew Beng Jin Teoh,et al.  Iris Authentication Using Privatized Advanced Correlation Filter , 2006, ICB.

[17]  N. Balakrishnan,et al.  Binomial and Negative Binomial Analogues under Correlated Bernoulli Trials , 1994 .

[18]  Andreas Uhl,et al.  A survey on biometric cryptosystems and cancelable biometrics , 2011, EURASIP J. Inf. Secur..

[19]  Dexin Zhang,et al.  Efficient iris recognition by characterizing key local variations , 2004, IEEE Transactions on Image Processing.

[20]  Emanuele Maiorana,et al.  Biometric cryptosystem using function based on-line signature recognition , 2010, Expert Syst. Appl..