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

Ying Han Pang, Andrew Teoh Beng Jin, David Ngo Chek Ling

Research output: Contribution to journalConference article

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)227-236
Number of pages10
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume3339
DOIs
Publication statusPublished - 2004 Jan 1
Event17th Australian Joint Conference on Artificial Intelligence, AI 2004: Advances in Artificial Intelligence - Cairns, Australia
Duration: 2004 Dec 42004 Dec 6

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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