Fuzzy Extractors for Minutiae-Based Fingerprint Authentication

Arakala, Arathi; Jeffers, Jason; Horadam, K. J.

doi:10.1007/978-3-540-74549-5_80

Cited by 73 publications

(48 citation statements)

References 11 publications

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“…Fuzzy key extraction schemes are classified under the key generation ones and they use helper data [53][54][55][56][57][58]. These schemes can be used as an authentication mechanism where a user is verified via her own biometric template as a key.…”

Section: Key Generation Systemsmentioning

confidence: 99%

THRIVE: threshold homomorphic encryption based secure and privacy preserving biometric verification system

Karabat

Kiraz

Erdoğan

et al. 2015

EURASIP J. Adv. Signal Process.

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In this paper, we introduce a new biometric verification and template protection system which we call THRIVE. The system includes novel enrollment and authentication protocols based on threshold homomorphic encryption where a private key is shared between a user and a verifier. In the THRIVE system, only encrypted binary biometric templates are stored in a database and verification is performed via homomorphically randomized templates, thus, original templates are never revealed during authentication. Due to the underlying threshold homomorphic encryption scheme, a malicious database owner cannot perform full decryption on encrypted templates of the users in the database. In addition, security of the THRIVE system is enhanced using a two-factor authentication scheme involving user's private key and biometric data. Using simulation-based techniques, the proposed system is proven secure in the malicious model. The proposed system is suitable for applications where the user does not want to reveal her biometrics to the verifier in plain form, but needs to prove her identity by using biometrics. The system can be used with any biometric modality where a feature extraction method yields a fixed size binary template and a query template is verified when its Hamming distance to the database template is less than a threshold. The overall connection time for the proposed THRIVE system is estimated to be 336 ms on average for 256-bit biometric templates on a desktop PC running with quad core 3.2 GHz CPUs at 10 Mbit/s up/down link connection speed. Consequently, the proposed system can be efficiently used in real-life applications.

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Section: Key Generation Systemsmentioning

confidence: 99%

THRIVE: threshold homomorphic encryption based secure and privacy preserving biometric verification system

Karabat

Kiraz

Erdoğan

et al. 2015

EURASIP J. Adv. Signal Process.

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“…While these two ideas sound good, practical implementation was not presented. Some researchers [28], [29] have followed this approach and proposed their own secure sketch and fuzzy extractor schemes.…”

Section: A Biometric Cryptosystems Approachmentioning

confidence: 99%

A Hybrid Approach for Generating Secure and Discriminating Face Template

Yan

Yuen

Jain

2010

IEEE Trans.Inform.Forensic Secur.

152

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Abstract-Biometric template protection is one of the most important issues in deploying a practical biometric system. To tackle this problem, many algorithms, that do not store the template in its original form, have been reported in recent years. They can be categorized into two approaches, namely biometric cryptosystem and transform-based. However, most (if not all) algorithms in both approaches offer a trade-off between the template security and matching performance. Moreover, we believe that no single template protection method is capable of satisfying the security and performance simultaneously. In this paper, we propose a hybrid approach which takes advantage of both the biometric cryptosystem approach and the transform-based approach. A three-step hybrid algorithm is designed and developed based on random projection, discriminability-preserving (DP) transform, and fuzzy commitment scheme. The proposed algorithm not only provides good security, but also enhances the performance through the DP transform. Three publicly available face databases, namely FERET, CMU-PIE, and FRGC, are used for evaluation. The security strength of the binary templates generated from FERET, CMU-PIE, and FRGC databases are 206.3, 203.5, and 347.3 bits, respectively. Moreover, noninvertibility analysis and discussion on data leakage of the proposed hybrid algorithm are also reported. Experimental results show that, using Fisherface to construct the input facial feature vector (face template), the proposed hybrid method can improve the recognition accuracy by 4%, 11%, and 15% on the FERET, CMU-PIE, and FRGC databases, respectively. A comparison with the recently developed random multispace quantization biohashing algorithm is also reported.

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“…The problem of generating fuzzy extractors from continuous distributions was addressed by Buhan et al [80]. Secure sketch construction for other modalities such as fingerprints [81,82], 3D face [83], and multimodal systems (face and fingerprint) [84] has also been proposed. Protocols for secure authentication in remote applications [85,86] have also been proposed based on the fuzzy extractor scheme.…”

Section: Key Generating Biometric Cryptosystemmentioning

confidence: 99%

Biometric template security

Nagar¹

2009

SPIE Newsroom

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Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorization of the various vulnerabilities of a biometric system and discuss countermeasures that have been proposed to address these vulnerabilities. In particular, we focus on biometric template security which is an important issue because, unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. Protecting the template is a challenging task due to intrauser variability in the acquired biometric traits. We present an overview of various biometric template protection schemes and discuss their advantages and limitations in terms of security, revocability, and impact on matching accuracy. A template protection scheme with provable security and acceptable recognition performance has thus far remained elusive. Development of such a scheme is crucial as biometric systems are beginning to proliferate into the core physical and information infrastructure of our society.

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Fuzzy Extractors for Minutiae-Based Fingerprint Authentication

Cited by 73 publications

References 11 publications

THRIVE: threshold homomorphic encryption based secure and privacy preserving biometric verification system

THRIVE: threshold homomorphic encryption based secure and privacy preserving biometric verification system

A Hybrid Approach for Generating Secure and Discriminating Face Template

Biometric template security

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