Biohashing: two factor authentication featuring fingerprint data and tokenised random number

Human authentication is the security task whose job is to limit access to physical locations or computer network only to those with authorisation. This is done by equipped authorised users with passwords, tokens or using their biometrics. Unfortunately, the first two suffer a lack of security as the...

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Main Authors: Jin, , ATB, Goh,, A, Ling, , DNC
Format: Article
Language:English
Published: 2004
Subjects:
Online Access:http://shdl.mmu.edu.my/2431/
http://shdl.mmu.edu.my/2431/1/1703.pdf
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author Jin, , ATB
Goh,, A
Ling, , DNC
author_facet Jin, , ATB
Goh,, A
Ling, , DNC
author_sort Jin, , ATB
building MMU Institutional Repository
collection Online Access
description Human authentication is the security task whose job is to limit access to physical locations or computer network only to those with authorisation. This is done by equipped authorised users with passwords, tokens or using their biometrics. Unfortunately, the first two suffer a lack of security as they are easy being forgotten and stolen; even biometrics also suffers from some inherent limitation and specific security threats. A more practical approach is to combine two or more factor authenticator to reap benefits in security or convenient or both. This paper proposed a novel two factor authenticator based on iterated inner products between tokenised pseudo-random number and the user specific fingerprint feature, which generated from the integrated wavelet and Fourier-Mellin transform, and hence produce a set of user specific compact code that coined as BioHashing. BioHashing highly tolerant of data capture offsets, with same user fingerprint data resulting in highly correlated bitstrings. Moreover, there is no deterministic way to get the user specific code without having both token with random data and user fingerprint 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. The BioHashing has significant functional advantages over solely biometrics i.e. zero equal error rate point and clean separation of the genuine and imposter populations, thereby allowing elimination of false accept rates without suffering from increased occurrence of false reject rates. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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spelling mmu-24312011-08-22T02:06:57Z http://shdl.mmu.edu.my/2431/ Biohashing: two factor authentication featuring fingerprint data and tokenised random number Jin, , ATB Goh,, A Ling, , DNC QA75.5-76.95 Electronic computers. Computer science Human authentication is the security task whose job is to limit access to physical locations or computer network only to those with authorisation. This is done by equipped authorised users with passwords, tokens or using their biometrics. Unfortunately, the first two suffer a lack of security as they are easy being forgotten and stolen; even biometrics also suffers from some inherent limitation and specific security threats. A more practical approach is to combine two or more factor authenticator to reap benefits in security or convenient or both. This paper proposed a novel two factor authenticator based on iterated inner products between tokenised pseudo-random number and the user specific fingerprint feature, which generated from the integrated wavelet and Fourier-Mellin transform, and hence produce a set of user specific compact code that coined as BioHashing. BioHashing highly tolerant of data capture offsets, with same user fingerprint data resulting in highly correlated bitstrings. Moreover, there is no deterministic way to get the user specific code without having both token with random data and user fingerprint 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. The BioHashing has significant functional advantages over solely biometrics i.e. zero equal error rate point and clean separation of the genuine and imposter populations, thereby allowing elimination of false accept rates without suffering from increased occurrence of false reject rates. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved. 2004-11 Article NonPeerReviewed application/pdf en http://shdl.mmu.edu.my/2431/1/1703.pdf Jin, , ATB and Goh,, A and Ling, , DNC (2004) Biohashing: two factor authentication featuring fingerprint data and tokenised random number. Pattern Recognition, 37 (11). pp. 2245-2255. ISSN 00313203 http://dx.doi.org/10.1016/j.patcog.2004.04.011 doi:10.1016/j.patcog.2004.04.011 doi:10.1016/j.patcog.2004.04.011
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Jin, , ATB
Goh,, A
Ling, , DNC
Biohashing: two factor authentication featuring fingerprint data and tokenised random number
title Biohashing: two factor authentication featuring fingerprint data and tokenised random number
title_full Biohashing: two factor authentication featuring fingerprint data and tokenised random number
title_fullStr Biohashing: two factor authentication featuring fingerprint data and tokenised random number
title_full_unstemmed Biohashing: two factor authentication featuring fingerprint data and tokenised random number
title_short Biohashing: two factor authentication featuring fingerprint data and tokenised random number
title_sort biohashing: two factor authentication featuring fingerprint data and tokenised random number
topic QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2431/
http://shdl.mmu.edu.my/2431/
http://shdl.mmu.edu.my/2431/
http://shdl.mmu.edu.my/2431/1/1703.pdf