CCS '99 Proceedings of the 6th ACM conference on Computer and communications security
Password hardening based on keystroke dynamics
CCS '99 Proceedings of the 6th ACM conference on Computer and communications security
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
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
Designs, Codes and Cryptography
Cancelable Biometrics: A Case Study in Fingerprints
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Fingerprint enhancement using STFT analysis
Pattern Recognition
Symmetric hash functions for fingerprint minutiae
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
K-plet and coupled BFS: a graph based fingerprint representation and matching algorithm
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Classification based revocable biometric identity code generation
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
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Since fingerprints provide a reliable alternative for traditional password based security systems, they gain industry and citizen acceptance. However, due to the higher uncertainty and inherent complexity associated with biometrics, using pure biometric traits does not present a reliable security system especially for large populations. This paper addresses this problem by proposing a hardening scheme which combines the fingerprint minutiae-based template and user-specific pseudo random data to enhance security. In the proposed scheme, a set of randomly selected user-specific chaff minutiae features are stored in a smartcard and a subset of this set is used at each acquisition. The set of chaff minutiae is combined with the template set and scrambled to form a fixed-length hardened feature. The graph based dynamic matching algorithm is transparent to the proposed hardening scheme anyhow it runs as if pure original template and query features are used. Our experiments show that biometric hardening reduces error rate to 0% with several orders of magnitude separation between genuine and impostor populations.