Guide to Biometrics
Enhancing security and privacy in biometrics-based authentication systems
IBM Systems Journal - End-to-end security
IEEE Transactions on Circuits and Systems for Video Technology
Theoretical Framework for Constructing Matching Algorithms in Biometric Authentication Systems
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
A Biometric Menagerie Index for Characterising Template/Model-Specific Variation
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
A study on security evaluation methodology for image-based biometrics authentication systems
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
A matching algorithm secure against the wolf attack in biometric authentication systems
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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This paper will propose a wolf attack probability (WAP) as a new measure for evaluating security of biometric authentication systems. The wolf attack is an attempt to impersonate a victim by feeding “wolves” into the system to be attacked. The “wolf” means an input value which can be falsely accepted as a match with multiple templates. WAP is defined as a maximum success probability of the wolf attack with one wolf sample. In this paper, we give a rigorous definition of the new security measure which gives strength estimation of an individual biometric authentication system against impersonation attacks. We show that if one reestimates using our WAP measure, a typical fingerprint algorithm turns out to be much weaker than theoretically estimated by Ratha et al. Moreover, we apply the wolf attack to a finger-vein-pattern based algorithm. Surprisingly, we show that there exists an extremely strong wolf which falsely matches all templates for any threshold value.