In order to ensure privacy constraints in biometrics, new algorithms called template protection schemes have been proposed in the last ten years in the literature. Most of these algorithms require as input a feature having a fixed size. Texture features can be used within this context for fingerprints as the number of minutiae varies in general for different captures. BioHashing is a two authentication factor algorithm that can be used to enhance to ensure privacy while using biometrics. In this work, we compare different recent texture features from the literature within the BioHashing scheme while considering many constraints: efficiency, maximal representation size and constant size description. Experiments are conducted on three fingerprint databases from the FVC competition. Results permit us to conclude on the texture features to be used within this context.
With more and more applications using biometrics, new privacy and security risks arise. Some new biometric systems have been proposed in the last decade following a privacy by design approach: cancelable biometric systems. Their evaluation is still an open issue in research. The objective of this paper is first to define an evaluation methodology for these particular biometric systems by proposing some metrics for testing their robustness. Second, we show through the example of a cancelable biometric system using finger-knuckle-prints how some privacy properties can be checked by simulating attacks.
The storage of fingerprints is an important issue as this biometric modality is more and more deployed for real applications. Considering minutiae templates as sensitive information, a key question concerns the secure and privacy management of this digital identity. Indeed, if an attacker obtains the minutiae template of an user, he/she will be able to generate a fingerprint having the same characteristics. Instead of directly storing the minutiae templates, we propose in this paper a new adaptation of BioHashing to generate a cancelable template in the context of un-ordered set of noisy minutiae features. To the authors knowledge, little interest has been paid in the literature to this question until now, since this is an acute problem. Using the
BioHashing is a popular biometric template protection scheme defined in the last decade. Most of previous studies on this algorithm focus on the performance optimization or the use of this privacy protection scheme on many types of biometric modalities (face, fingerprint, palmprint.. .). The objective of this paper is to study the robustness of this algorithm on a texture based representation by testing and simulating operational attacks. We consider in this study some quantitative measures of the robustness of the BioHashing algorithm and we show some new results on its security on fingerprints represented by texture features.
We address in this paper the problem of privacy in the current architecture in electronic passports for the storage and transmission of biometric data such as fingerprints. The current architecture provides a good protection of biometric personal data but brute force attack could be used in a near future using cloud computing. We propose a new solution combining cryptographic protocols and cancelable biometrics. The indivdual's biocode in protected by cryptographic keys exchanged by the PACE protocol. We put into obviousness the benefit of the proposed solution in terms of security and privacy.
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