Random Multispace Quantization as an Analytic Mechanism for BioHashing of Biometric and Random Identity Inputs

Teoh, Andrew Beng Jin; Goh, Alwyn; Ngo, David Chek Ling

doi:10.1109/tpami.2006.250

Cited by 406 publications

(182 citation statements)

References 25 publications

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“…However, Kong et al showed later in [KCZ * 06] that the recognition performance is degraded in comparison with the unprotected features in the case that projection matrix is stolen and used by impostor. This algorithm is further implemented for palm recognition [CTGN05], face recognition [TwGdCN06] etc.…”

Section: Biometric Template Protectionmentioning

confidence: 99%

Privacy and Security Assessment of Biometric Template Protection

Zhou¹

2012

Itit

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Throughout the ages all those who have been highly successful in great ventures and in the pursuit of great learning must have successfully undergone three stages:"Last night the west wind shriveled the green-clad trees; alone I climb the high tower, to gaze at the road stretching to the horizon" represents the first stage."I have no regrets as my girdle grows looser on my waist; with everlasting love I pine for you" represents the second stage."I have sought her in the crowd a hundred, a thousand times; suddenly turning back my head, I see her under the dimming lanterns" represents the third stage. Erklärung zur DissertationHiermit versichere ich die vorliegende Dissertation selbständig nur mit den angegebenen Quellen und Hilfsmitteln angefertigt zu haben. Alle Stellen, die aus Quellen entnommen wurden, sind als solche kenntlich gemacht. Diese Arbeit hat in gleicher oder ähnlicher Form noch keiner Prüfungsbehörde vorgelegen.Darmstadt, den 4. August 2011 Xuebing Zhou AbstractBiometrics enables convenient authentication based on a person's physical or behavioral characteristics. In comparison with knowledge-or token-based methods, it links an identity directly to its owner. Furthermore, it can not be forgotten or handed over easily. As biometric techniques have become more and more efficient and accurate, they are widely used in numerous areas. Among the most common application areas are physical and logical access controls, border control, authentication in banking applications and biometric identification in forensics.In this growing field of biometric applications, concerns about privacy and security cannot be neglected. The advantages of biometrics can revert to the opposite easily. The potential misuse of biometric information is not limited to the endangerment of user privacy, since biometric data potentially contain sensitive information like gender, race, state of health, etc. Different applications can be linked through unique biometric data. Additionally, identity theft is a severe threat to identity management, if revocation and reissuing of biometric references are practically impossible. Therefore, template protection techniques are developed to overcome these drawbacks and limitations of biometrics. Their advantage is the creation of multiple secure references from biometric data. These secure references are supposed to be unlinkable and non-invertible in order to achieve the desired level of security and to fulfill privacy requirements.The existing algorithms can be categorized into transformation-based approaches and biometric cryptosystems. The transformation-based approaches deploy different transformation or randomization functions, while the biometric cryptosystems construct secrets from biometric data. The integration in biometric systems is commonly accepted in research and their feasibility according to the recognition performance is proved. Despite of the success of biometric template protection techniques, their security and privacy properties are investigated only limitedly.This predomin...

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Section: Biometric Template Protectionmentioning

confidence: 99%

Privacy and Security Assessment of Biometric Template Protection

Zhou¹

2012

Itit

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“…Randomized dynamic quantization transformation comprises of three steps: (1) Random Projection [5], (2) Dynamic Quantization and (3) Condensation.…”

Section: Randomized Dynamic Quantization Transformationmentioning

confidence: 99%

Secure biometric template protection in fuzzy commitment scheme

Teoh

Kim

2007

IEICE Electron. Express

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Fuzzy Commitment Scheme is a popular technique for biometric template protection. The idea is to bind an random bit string with a biometric template in binary format called difference vector. Ideally, a difference vector is infeasible to recover either the biometric template or the random bit string without any knowledge of the user's biometric data. Yet, this is only valid if the biometric template is uniformly random, which is not the case in reality. In this paper, we propose a method known as Randomized Dynamic Quantization transformation to binarize biometric data. The transformed bit strings are highly distinctive among the users and near to uniformly random. We demonstrate the implementation in the context of fingerprint biometrics.

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“…The template protection schemes proposed in literatures can be broadly classified into two categories, feature transformation approach and biometric cryptosystem [2], [3]. The former [4]- [16] has a high degree of freedom for signal processing in the protected domain, compared to the latter [17]- [21]. Feature transform schemes can be further categorized as salting biometric [4]- [8] and noninvertible [9]- [16] transforms.…”

Section: Introductionmentioning

confidence: 99%

Unitary Transform-Based Template Protection and Its Application to <i>l</i><sup>2</sup>-norm Minimization Problems

Nakamura

Tonomura

Kiya

2016

IEICE Trans. Inf. & Syst.

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SUMMARYWe focus on the feature transform approach as one methodology for biometric template protection, where the template consists of the features extracted from the biometric trait. This study considers some properties of the unitary (including orthogonal) transform-based template protection in particular. It is known that the Euclidean distance between the templates protected by a unitary transform is the same as that between original (non-protected) ones as a property. In this study, moreover, it is shown that it provides the same results in l 2 -norm minimization problems as those of original templates. This means that there is no degradation of recognition performance in authentication systems using l 2 -norm minimization. Therefore, the protected templates can be reissued multiple times without original templates. In addition, a DFT-based template protection scheme is proposed as an unitary transform-based one. The proposed scheme enables to efficiently generate protected templates by the FFT, in addition to the useful properties. It is also applied to face recognition experiments to evaluate the effectiveness.

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Random Multispace Quantization as an Analytic Mechanism for BioHashing of Biometric and Random Identity Inputs

Cited by 406 publications

References 25 publications

Privacy and Security Assessment of Biometric Template Protection

Privacy and Security Assessment of Biometric Template Protection

Secure biometric template protection in fuzzy commitment scheme

Unitary Transform-Based Template Protection and Its Application to <i>l</i><sup>2</sup>-norm Minimization Problems

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