Collisionful keyed hash functions with selectable collisions
Information Processing Letters
Making, Breaking Codes: Introduction to Cryptology
Making, Breaking Codes: Introduction to Cryptology
Icsa Guide to Cryptography
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
An improved BioHashing for human authentication
Pattern Recognition
Remarks on BioHash and its mathematical foundation
Information Processing Letters
Illumination Invariant Face Recognition Using Near-Infrared Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Random subspace for an improved BioHashing for face authentication
Pattern Recognition Letters
Cancellable biometrics and annotations on BioHash
Pattern Recognition
Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data
SIAM Journal on Computing
Revealing the secret of facehashing
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
IEEE Transactions on Circuits and Systems for Video Technology
Learning multi-scale block local binary patterns for face recognition
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Iris-Biometric fuzzy commitment schemes under signal degradation
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
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Biometric encryption is the basis for biometric template protection and information security. While existing methods are based on iris or fingerprint modality, face has so far been considered not reliable enough to meet the requirement for error correcting ability. In this paper, we present a novel biometric key binding method based on near infrared (NIR) face biometric. An enhanced BioHash algorithm is developed by imposing an NXOR mask onto the input to the subsequent error correcting code (ECC). This way, when combined with ECC and NIR face features, it enables reliable binding of face biometric features and the biometric key. Its ability for template protection and information cryptography is guarantied by the theory of encryption. The security level of NIR face recognition system is thereby improved. Experimental results show that the security benefit is gained with a sacrifice of 1-2% drop in the recognition performance.