Secure Sketch for Multiple Secrets

Fang, Chengfang; Chang, Ee-Chien

doi:10.1007/978-3-642-13708-2_22

Cited by 5 publications

(3 citation statements)

References 23 publications

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“…This approach is similar to the package model proposed in [16], which in turn is based on the AND decision fusion rule. Fang et al [32] consider a more general version of the above modular approach, where multiple secrets (could be biometric templates or passwords) are mixed in a cascaded fashion within the secure sketch framework. One advantage of such a modular approach is that additional biometric traits can be easily introduced in the multibiometric cryptosystem.…”

Section: Multibiometric Cryptosystemsmentioning

confidence: 99%

Multibiometric Cryptosystems Based on Feature-Level Fusion

Nagar

Nandakumar

Jain

2012

IEEE Trans.Inform.Forensic Secur.

245

162

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Abstract-Multibiometric systems are being increasingly deployed in many large scale biometric applications (e.g., FBI-IAFIS, UIDAI system in India) because they have several advantages such as lower error rates and larger population coverage compared to unibiometric systems. However, multibiometric systems require storage of multiple biometric templates (e.g., fingerprint, iris, and face) for each user, which results in increased risk to user privacy and system security. One method to protect individual templates is to store only the secure sketch generated from the corresponding template using a biometric cryptosystem. This requires storage of multiple sketches. In this paper, we propose a feature level fusion framework to simultaneously protect multiple templates of a user as a single secure sketch. Our main contributions include: (i) practical implementation of the proposed feature level fusion framework using two wellknown biometric cryptosystems, namely, fuzzy vault and fuzzy commitment, and (ii) detailed analysis of the trade-off between matching accuracy and security in the proposed multibiometric cryptosystems based on two different databases (one real and one virtual multimodal database), each containing the three most popular biometric modalities, namely, fingerprint, iris, and face. Experimental results show that both the multibiometric cryptosystems proposed here have higher security and matching performance compared to their unibiometric counterparts.

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Section: Multibiometric Cryptosystemsmentioning

confidence: 99%

Multibiometric Cryptosystems Based on Feature-Level Fusion

Nagar

Nandakumar

Jain

2012

IEEE Trans.Inform.Forensic Secur.

245

162

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“…Alignment-free features extracted are less sensitive to the triangular approach and are applied directly only to template protection. Fang, et al [15] developed a cascaded method within the sketch of a secure framework. The main advantage of the proposed approach is that biometric feature data can easily be combined with a multi-biometric cryptosystem.…”

Section: Introductionmentioning

confidence: 99%

Multimodal Biometric Template Transformation Approach using a List Ranking Algorithm

Bharathi

Sarika

et al. 2022

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User authentication has become vital with the advancement in technologies that comes with an increased threat to security. Biometrics is typically used to secure the data of individuals based on their unique features, such as fingerprints, retinas, and hand geometry. Template transformation is a technique in which the original feature vectors are transformed into modified feature vectors. When these templates are transformed and stored, it becomes difficult for imposters to hack the system. Existing systems store and secure these templates based on key generation. When the key information is compromised, the system can be easily hacked. Hence, in the proposed system, the templates are transformed using a modified list ranking algorithm and then stored for verification. Also, in order to improve security, instead of using a single biometric, the proposed system obtains biometric data from left fingerprints, right fingerprints and palm prints and fuses them into a single feature vector set. Thus, even when the repository is attacked, it would be very difficult to break into the system. The proposed system provides a 2.9 % equal error rate compared with existing systems.

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“…This approach is similar to the package model proposed in [49], which in turn is based on the AND decision fusion rule. Fang et al [37] consider a more general version of the above modular approach, where multiple secrets (could be biometric templates or passwords) are mixed in a cascaded fashion within the secure sketch framework. One advantage of such a modular approach is that additional biometric traits can be easily introduced in the multibiometric cryptosystem.…”

Section: Introductionmentioning

confidence: 99%

Biometric Template Security

Jain¹,

Nandakumar²,

Nagar³

2008

EURASIP J Adv Signal Process

934

665

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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 bio-metric systems are beginning to proliferate into the core physical and information infrastructure of our society.

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Secure Sketch for Multiple Secrets

Cited by 5 publications

References 23 publications

Multibiometric Cryptosystems Based on Feature-Level Fusion

Multibiometric Cryptosystems Based on Feature-Level Fusion

Multimodal Biometric Template Transformation Approach using a List Ranking Algorithm

Biometric Template Security

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