Personal authenticator on the basis of two-factors: palmprint features and tokenized random data

Authors:
Ying-Han Pang;Andrew Teoh Beng Jin;David Ngo Chek Ling
Affiliations:
Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia;Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia;Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia
Venue:
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Year:
2004

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Letters: Multihashing, human authentication featuring biometrics data and tokenized random number: A case study FVC2004

Neurocomputing

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Abstract

This paper presents a novel two-factor authenticator which hashes tokenized random data and moment based palmprint features to produce a set of private binary string, coined as Discrete-Hashing code This novel technique requires two factors (random number + authorized biometrics) credentials in order to access the authentication system Absence of either factor will just handicap the progress of authentication Besides that, Discrete-Hashing also possesses high discriminatory power, with highly correlated bit strings for intra-class data Experimental results show that this two-factor authenticator surpasses the classic biometric authenticator in terms of verification rate Our proposed approach provides a clear separation between genuine and imposter population distributions This implies that Discrete-Hashing technique allows achievement of zero False Accept Rate (FAR) without jeopardizing the False Reject Rate (FRR) performance, which is hardly possible to conventional biometric systems.