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97
Fuzzy extractors
 In Security with Noisy Data
, 2007
"... This chapter presents a general approach for handling secret biometric data in cryptographic applications. The generality manifests itself in two ways: we attempt to minimize the assumptions we make about the data, and to present techniques that are broadly applicable wherever biometric inputs are u ..."
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Cited by 5 (2 self)
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This chapter presents a general approach for handling secret biometric data in cryptographic applications. The generality manifests itself in two ways: we attempt to minimize the assumptions we make about the data, and to present techniques that are broadly applicable wherever biometric inputs are used. Because biometric data comes from a variety of sources that are mostly outside of anyone’s control, it is prudent to assume as little as possible about how they are distributed; in particular, an adversary may know more about a distribution than a system’s designers and users. Of course, one may attempt to measure some properties of a biometric distribution, but relying on such measurements in the security analysis is dangerous, because the adversary may have even more accurate measurements available to it. For instance, even assuming that some property of a biometric behaves according to a binomial distribution (or some similar discretization of the normal distribution), one could determine the mean of this distribution only to within ≈ 1 √ after taking n n samples; a wellmotivated adversary can take more measurements, and thus determine the mean more accurately.
Fuzzy extractor
, 2013
"... a b s t r a c t Biocryptography is an emerging security technology which combines cryptography with biometrics. A good biocryptosystem is required to protect the privacy of the relevant biometric data as well as achieving high recognition accuracy. Fingerprints have been widely used in biocryptos ..."
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a b s t r a c t Biocryptography is an emerging security technology which combines cryptography with biometrics. A good biocryptosystem is required to protect the privacy of the relevant biometric data as well as achieving high recognition accuracy. Fingerprints have been widely used in biocryptosystem design. However, fingerprint uncertainty caused by distortion and rotation during the image capturing process makes it difficult to achieve a high recognition rate in most biocryptographic systems. Moreover, most existing biocryptosystems rely on the accurate detection of singular points for fingerprint image prealignment, which is very hard to achieve, and the image rotation transformation during the alignment process can cause significant singular point deviation and minutiae changes. In this paper, by taking full advantage of local Voronoi neighbor structures (VNSs), e.g. local structural stability and distortion insensitivity, we propose an alignmentfree biocryptosystem based on fixedlength bitstring representations extracted from modified VNSs, which are rotation and translationinvariant and distortion robust. The proposed alignmentfree biocryptosystem is able to provide strong security while achieving good recognition performance. Experimental results in comparison with most existing alignmentfree biocryptosystems using the publiclyavailable databases show the validity of the proposed scheme. & 2013 Elsevier Ltd. All rights reserved. 1.
Reusable cryptographic fuzzy extractors
 ACM CCS 2004, ACM
, 2004
"... We show that a number of recent definitions and constructions of fuzzy extractors are not adequate for multiple uses of the same fuzzy secret—a major shortcoming in the case of biometric applications. We propose two particularly stringent security models that specifically address the case of fuzzy s ..."
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Cited by 96 (2 self)
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We show that a number of recent definitions and constructions of fuzzy extractors are not adequate for multiple uses of the same fuzzy secret—a major shortcoming in the case of biometric applications. We propose two particularly stringent security models that specifically address the case of fuzzy
On the Limits of Computational Fuzzy Extractors
, 2014
"... Fuller et. al (Asiacrypt 2013) studied on computational fuzzy extractors, and showed, as a negative result, that the existence of a computational "secure sketch" implies the existence of an informationtheoretically secure sketch with slightly weaker parameters. In this work, we show a sim ..."
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Fuller et. al (Asiacrypt 2013) studied on computational fuzzy extractors, and showed, as a negative result, that the existence of a computational "secure sketch" implies the existence of an informationtheoretically secure sketch with slightly weaker parameters. In this work, we show a
When are Fuzzy Extractors Possible?
, 2014
"... Fuzzy extractors (Dodis et al., Eurocrypt 2004) convert repeated noisy readings of a highentropy secret into the same uniformly distributed key. A minimum condition for the security of the key is the hardness of guessing a value that is similar to the secret, because the fuzzy extractor converts su ..."
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Fuzzy extractors (Dodis et al., Eurocrypt 2004) convert repeated noisy readings of a highentropy secret into the same uniformly distributed key. A minimum condition for the security of the key is the hardness of guessing a value that is similar to the secret, because the fuzzy extractor converts
Strongly Robust Fuzzy Extractors
"... Fuzzy extractors are used to generate reliably reproducible randomness from a biased, noisy source. Known constructions of fuzzy extractors are built from a strong extractor, and a secure sketch, a function that transforms a biased noisy secret value into a public value, simultaneously hiding the se ..."
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Fuzzy extractors are used to generate reliably reproducible randomness from a biased, noisy source. Known constructions of fuzzy extractors are built from a strong extractor, and a secure sketch, a function that transforms a biased noisy secret value into a public value, simultaneously hiding
Fuzzy extractors for continuous distributions
 Proceedings of the 2nd ACM Symposium on Information, Computer and Communications Security (ASIACCS), Singapore
, 2007
"... We show that there is a direct relation between the maximum length of the keys extracted from biometric data and the error rates of the biometric system. The length of the biokey depends on the amount of distinguishing information that can be extracted from the source data. This information can be ..."
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Cited by 18 (2 self)
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be used apriori to evaluate the potential of the biometric data in the context of a specific cryptographic application. We model the biometric data more naturally as a continuous distribution and we give a new definition for fuzzy extractors that works better for this type of data. 1
Computational Fuzzy Extractors
, 2013
"... Fuzzy extractors derive strong keys from noisy sources. Their security is defined informationtheoretically, which limits the length of the derived key, sometimes making it too short to be useful. We ask whether it is possible to obtain longer keys by considering computational security, and show the ..."
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Cited by 3 (1 self)
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Fuzzy extractors derive strong keys from noisy sources. Their security is defined informationtheoretically, which limits the length of the derived key, sometimes making it too short to be useful. We ask whether it is possible to obtain longer keys by considering computational security, and show
Trapdoor Computational Fuzzy Extractors
, 2014
"... We describe a method of cryptographicallysecure key extraction from a noisy biometric source. The computational security of our method can be clearly argued through hardness of Learning Parity With Noise (LPN). We use a fuzzy commitment scheme so the extracted key is chosen by definition to have ..."
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of biometric bits. The confidence information is never exposed and is used as a noiseavoiding trapdoor to exponentially reduce key recovery complexity. Previous computational fuzzy extractors were unable to correct Θ(m) errors or would run in exponential time in m. A second key result is that we relax
Fuzzy extractors: How to generate strong keys from biometrics and other noisy data
, 2008
"... We provide formal definitions and efficient secure techniques for • turning noisy information into keys usable for any cryptographic application, and, in particular, • reliably and securely authenticating biometric data. Our techniques apply not just to biometric information, but to any keying mater ..."
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Cited by 535 (38 self)
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material that, unlike traditional cryptographic keys, is (1) not reproducible precisely and (2) not distributed uniformly. We propose two primitives: a fuzzy extractor reliably extracts nearly uniform randomness R from its input; the extraction is errortolerant in the sense that R will be the same even
Results 1  10
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