Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
CCS '99 Proceedings of the 6th ACM conference on Computer and communications security
Secure smartcardbased fingerprint authentication
WBMA '03 Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications
Enhancing security and privacy in biometrics-based authentication systems
IBM Systems Journal - End-to-end security
Robust Distance Measures for Face-Recognition Supporting Revocable Biometric Tokens.
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Cancelable Biometrics: A Case Study in Fingerprints
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Biometrics: a tool for information security
IEEE Transactions on Information Forensics and Security
Biometric hash: high-confidence face recognition
IEEE Transactions on Circuits and Systems for Video Technology
A hybrid approach for generating secure and discriminating face template
IEEE Transactions on Information Forensics and Security
A Hybrid Approach for Biometric Template Security
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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This paper addresses the biometric template security issue. Follow out previous work on class distribution transform, the proposed scheme selects the distinguish points automatically. By considering the geometric relationship with the biometric templates, the proposed scheme transforms a real-value biometric template to a binary string such that the class distribution is preserved and proved mathematically. The binary string is then further encoded using BCH and hashing method to ensure that the template protecting algorithm is non-invertible. Two face databases, namely ORL and FERET, are selected for evaluation and LDA is used for creating the original template. Experimental results show that by integrating the proposed scheme into the LDA (original) algorithm, the system performance can be further improved by 1.1% and 4%, in terms of equal error rate, on ORL and FERET databases respectively. The results show that the proposed scheme not only can preserve the original template discriminant power, but also improve the performance if the original template is not fully optimized.