An integrated dual factor authenticator based on the face data and tokenised random number

This paper proposed a novel integrated dual factor authenticator based on iterated inner products between tokenised pseudo random number and the user specific facial feature, which generated from a well known subspace feature extraction technique-Fisher Discriminant Analysis, and hence produce a set...

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Main Authors: Teoh, , ABJ, Goh,, A, Ngo, , DCL
Format: Article
Published: 2004
Subjects:
Online Access:http://shdl.mmu.edu.my/2501/
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author Teoh, , ABJ
Goh,, A
Ngo, , DCL
author_facet Teoh, , ABJ
Goh,, A
Ngo, , DCL
author_sort Teoh, , ABJ
building MMU Institutional Repository
collection Online Access
description This paper proposed a novel integrated dual factor authenticator based on iterated inner products between tokenised pseudo random number and the user specific facial feature, which generated from a well known subspace feature extraction technique-Fisher Discriminant Analysis, and hence produce a set of user specific compact code that coined as BioCode. The BioCode highly tolerant of data captures offsets, with same user facial data resulting in highly correlated bitstrings. Moreover, there is no deterministic way to get the user specific code without having both tokenised random data and user facial feature. This would protect us for instance against biometric fabrication by changing the user specific credential, is as simple as changing the token containing the random data. This approach has significant functional advantages over solely biometrics ie. zero EER point and clean separation of the genuine and imposter populations, thereby allowing elimination of FARs without suffering from increased occurrence of FRRs.
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spelling mmu-25012011-08-22T02:46:00Z http://shdl.mmu.edu.my/2501/ An integrated dual factor authenticator based on the face data and tokenised random number Teoh, , ABJ Goh,, A Ngo, , DCL QA75.5-76.95 Electronic computers. Computer science This paper proposed a novel integrated dual factor authenticator based on iterated inner products between tokenised pseudo random number and the user specific facial feature, which generated from a well known subspace feature extraction technique-Fisher Discriminant Analysis, and hence produce a set of user specific compact code that coined as BioCode. The BioCode highly tolerant of data captures offsets, with same user facial data resulting in highly correlated bitstrings. Moreover, there is no deterministic way to get the user specific code without having both tokenised random data and user facial feature. This would protect us for instance against biometric fabrication by changing the user specific credential, is as simple as changing the token containing the random data. This approach has significant functional advantages over solely biometrics ie. zero EER point and clean separation of the genuine and imposter populations, thereby allowing elimination of FARs without suffering from increased occurrence of FRRs. 2004 Article NonPeerReviewed Teoh, , ABJ and Goh,, A and Ngo, , DCL (2004) An integrated dual factor authenticator based on the face data and tokenised random number. BIOMETRIC AUTHENTICATION, PROCEEDINGS, 3072 . pp. 117-123. ISSN 0302-9743
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Teoh, , ABJ
Goh,, A
Ngo, , DCL
An integrated dual factor authenticator based on the face data and tokenised random number
title An integrated dual factor authenticator based on the face data and tokenised random number
title_full An integrated dual factor authenticator based on the face data and tokenised random number
title_fullStr An integrated dual factor authenticator based on the face data and tokenised random number
title_full_unstemmed An integrated dual factor authenticator based on the face data and tokenised random number
title_short An integrated dual factor authenticator based on the face data and tokenised random number
title_sort integrated dual factor authenticator based on the face data and tokenised random number
topic QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2501/