CCS '99 Proceedings of the 6th ACM conference on Computer and communications security
The FERET Evaluation Methodology for Face-Recognition Algorithms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
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
Cancelable Biometric Filters for Face Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
A secure biometric authentication scheme based on robust hashing
MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
AUTOID '05 Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies
IEEE Transactions on Knowledge and Data Engineering
Combining Crypto with Biometrics Effectively
IEEE Transactions on Computers
IEEE Transactions on Pattern Analysis and Machine Intelligence
An analysis of BioHashing and its variants
Pattern Recognition
Journal of Cognitive Neuroscience
Cancellable biometerics featuring with tokenised random number
Pattern Recognition Letters
New shielding functions to enhance privacy and prevent misuse of biometric templates
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Revealing the secret of facehashing
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Generation of replaceable cryptographic keys from dynamic handwritten signatures
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Cancelable key-based fingerprint templates
ACISP'05 Proceedings of the 10th Australasian conference on Information Security and Privacy
Practical biometric authentication with template protection
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
An analysis on accuracy of cancelable biometrics based on biohashing
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Near Infrared Face Based Biometric Key Binding
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
A performance driven methodology for cancelable face templates generation
Pattern Recognition
A Comparative Study of Palmprint Recognition Algorithms
ACM Computing Surveys (CSUR)
Mobile device integration of a fingerprint biometric remote authentication scheme
International Journal of Communication Systems
A secure biometric discretization scheme for face template protection
Future Generation Computer Systems
Investigating fusion approaches in multi-biometric cancellable recognition
Expert Systems with Applications: An International Journal
Distance entropy as an information measure for binary biometric representation
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Enhanced multi-line code for minutiae-based fingerprint template protection
Pattern Recognition Letters
Two-factor face authentication using matrix permutation transformation and a user password
Information Sciences: an International Journal
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Lately, the once powerful one-factor authentication which is based solely on either password, token or biometric approach, appears to be insufficient in addressing the challenges of identity frauds. For example, the sole biometric approach suffers from the privacy invasion and non-revocable issues. Passwords and tokens are easily forgotten and lost. To address these issues, the notion of cancellable biometrics was introduced to denote biometric templates that can be cancelled and replaced with the inclusion of another independent authentication factor. BioHash is a form of cancellable biometrics which mixes a set of user-specific random vectors with biometric features. In verification setting, BioHash is able to deliver extremely low error rates as compared to the sole biometric approach when a genuine token is used. However, this raises the possibility of two identity theft scenarios: (i) stolen-biometrics, in which an impostor possesses intercepted biometric data of sufficient high quality to be considered genuine and (ii) stolen-token, in which an impostor has access to the genuine token and used by the impostor to claim as the genuine user. We found that the recognition rate for the latter case is poorer. In this paper, the quantised random projection ensemble based on the Johnson-Lindenstrauss Lemma is used to establish the mathematical foundation of BioHash. Based on this model, we elucidate the characteristics of BioHash in pattern recognition as well as security view points and propose new methods to rectify the stolen-token problem.