Security Considerations in Minutiae-Based Fuzzy Vaults

Tams, Benjamin; Mihăilescu, Preda; Munk, Axel

doi:10.1109/tifs.2015.2392559

Cited by 73 publications

(50 citation statements)

References 38 publications

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“…In order to optimize the success rate, the attacker can deviate from the parameters used in actual operation; however, in the proposed scheme, the number of decoding iterations is the only parameter that is not already fixed at the time of enrolment. It has been proven in [68] that the expected number of decoding attempts of the false-accept attack is minimized for using one iteration. Moreover, it has been shown that an attacker's success probability is maximized by using simple polynomial interpolation as opposed to using a Reed-Solomon decoder.…”

Section: Database and Experimental Methodsmentioning

confidence: 99%

“…This property allows us to give heuristic estimates of FMRs that are much smaller than 1/I: For each single impostor verification, we compute the success probability based on the size of the unlocking set and the number of correct points contained, and finally, we estimate the FMR as the mean over all verifications. For details, we refer to [68].…”

Section: Database and Experimental Methodsmentioning

confidence: 99%

“…Moreover, the use of public unprotected auxiliary alignment data can ease an attacker in performing linkage attacks. As a countermeasure, an implementation for absolutely pre-aligned minutiae that avoids any correlation between related records of the fuzzy vault scheme has been proposed [68]. Another advantage from the construction in [68] is that the improved fuzzy vault scheme by Dodis et al [69] can be used for template protection which results in significantly more compact record sizes.…”

Section: Fuzzy Vault Schemementioning

confidence: 99%

“…As a countermeasure, an implementation for absolutely pre-aligned minutiae that avoids any correlation between related records of the fuzzy vault scheme has been proposed [68]. Another advantage from the construction in [68] is that the improved fuzzy vault scheme by Dodis et al [69] can be used for template protection which results in significantly more compact record sizes. Compared to earlier works [63,64], security levels have been revealed to be approximately 40 bits for single-finger fuzzy vaults.…”

Section: Fuzzy Vault Schemementioning

confidence: 99%

“…Though, in the original fuzzy vault [23,62], a Reed-Solomon decoder [72] has been proposed, its resulting error-correcting capabilities are not sufficient to achieve a practical implementation for single finger. As a consequence, the use of a Lagrange-based decoder has been proposed [64] and adopted for other single-finger implementations [65,68]. A multi-finger implementation has been proposed in [71].…”

Section: Fuzzy Vault Schemementioning

confidence: 99%

See 4 more Smart Citations

Unlinkable improved multi-biometric iris fuzzy vault

Rathgeb

Tams²,

Wagner

et al. 2016

EURASIP J. on Info. Security

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Iris recognition technologies are deployed in numerous large-scale nation-wide projects in order to provide robust and reliable biometric recognition of individuals. Moreover, the iris has been found to be rather stable over time, i.e. iris biometric reference data provides a strong and permanent link between individuals and their biometric traits. Hence, unprotected storage of (iris) biometric data provokes serious privacy threats, e.g. identity theft, limited re-newability, or cross-matching. Biometric cryptosystems grant a significant improvement in data privacy and increase the likelihood that individuals will effectively consent in the biometric system usage. However, the vast majority of proposed biometric cryptosystems do not guarantee desired properties of irreversibility, unlinkability, and re-newability without significantly degrading the biometric performance. In this work, we propose an unlinkable multi-instance iris biometric cryptosystem based on the improved fuzzy vault scheme. The proposed system locks biometric feature sets extracted from binary iris biometric reference data, i.e. iris-codes, of the left and right irises in a single fuzzy vault. In order to retain the size of the protected template and authentication speed, the proposed fusion step combines the most discriminative parts of two iris-codes at feature level. It is shown that the proposed key-binding process enables the generation of irreversible protected templates which prevents from previously proposed cross-matching attacks. Further, we investigate the optimal choice among potential decoding strategies with respect to biometric performance and time of key retrieval. The fully reproducible system is integrated to two different publicly available iris recognition systems and evaluated on the CASIAv3-Interval and the IITDv1 iris databases. Compared to the corresponding unprotected recognition schemes, genuine match rates of approximately 95 and 97 % at which no false accepts are observed and maintained in a single-and multi-instance scenario, respectively. Moreover, the multi-iris system is shown to significantly improve privacy protection achieving security levels of approximately 70 bits at practical biometric performance.

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Section: Database and Experimental Methodsmentioning

confidence: 99%

Section: Database and Experimental Methodsmentioning

confidence: 99%