Efficient, Reusable Fuzzy Extractors from LWE

Apon, Daniel; Cho, Chongwon; Eldefrawy, Karim; Katz, Jonathan

doi:10.1007/978-3-319-60080-2_1

Cited by 41 publications

(13 citation statements)

References 10 publications

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“…Recently, several reusable fuzzy extractor schemes have been introduced [32], [34]- [36]. In [34]- [36], the size of the helper data has been reduced compared to [1], but they are not capable of handling the outliers in the user's fuzzy data. In [32], Cheon et al have modified the reusable fuzzy extractor proposed in [1] and reduced the size of helper data by adopting a threshold scheme.…”

Section: Discussionmentioning

confidence: 99%

Fuzzy Vector Signature and Its Application to Privacy-Preserving Authentication

et al. 2019

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Fuzzy authentication uses non-deterministic or noisy data, like biometrics, as an authentication factor. Although the data is extracted from the same individual or source, it can be different for each measurement. As a result, one of the main issues in fuzzy authentication is the effective processing of the fuzziness, while guaranteeing the privacy of the fuzzy data. Biometric data is a typical user-generated fuzzy data and the fuzzy extractor is one of the most promising primitives for biometric authentication these days. In 2016, Canetti et al. proposed the reusable fuzzy extractor, in which multiple keys can be generated with the same biometric data. It can also handle some outliers which occur unexpectedly (owing to an external interference when acquiring the fuzzy data, for example, the presence of dust on a fingerprint image). However, the size of the user's helper data in the reusable fuzzy extractor is quite large. This makes the network bandwidth usage required in the online authentication phase (or the storage required on the user side) considerable, which inconveniences the user. In this paper, we present a new primitive for fuzzy authentication, called a fuzzy vector signature (FVS) scheme, which significantly alleviates the burden on the user side. This means that the network bandwidth usage (or the amount of storage required on the user side) is significantly reduced. The proposed FVS scheme is reusable and robust to outliers as well. Finally, we provide a privacy-preserving fuzzy authentication protocol based on the FVS scheme.

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Section: Discussionmentioning

confidence: 99%

Fuzzy Vector Signature and Its Application to Privacy-Preserving Authentication

et al. 2019

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“…Apon et al [ACEK17], Herder et. al [HRvD + 17] and Wen and Liu [WL18] use random linear codes to provide reusability.…”

Section: Subsequent Reusable Fuzzy Extractorsmentioning

confidence: 98%

“…In particular, shift secure constructions tend to consider adaptive security. Shift correlation secure constructions are known from assumptions such as decisional Diffie-Hellman [WLH18] and learning with errors [WL18,ACEK17] while known arbitrary correlation constructions rely on digital lockers.…”

Section: Defining Reusabilitymentioning

confidence: 99%

Reusable Fuzzy Extractors for Low-Entropy Distributions

et al. 2020

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“…Apon et al [ACEK17] showed that the construction presented in this paper achieves a weak form of reusability if it is modified so that the random code is a global parameter (instead of being created as part of Gen). They also show how to augment the reusability using either a random oracle or LWEbased symmetric encryption techniques.…”

Section: Subsequent Workmentioning

confidence: 99%

Computational fuzzy extractors

Fuller

Meng

Reyzin

2020

Information and Computation

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Fuzzy extractors derive strong keys from noisy sources. Their security is usually defined informationtheoretically, with gaps between known negative results, existential constructions, and polynomial-time constructions. We ask whether using computational security can close these gaps. We show the following: • Negative Result: Noise tolerance in fuzzy extractors is usually achieved using an information reconciliation component called a secure sketch. We show that secure sketches are subject to upper bounds from coding theory even when the information-theoretic security requirement is relaxed. Specifically, we define computational secure sketches using conditional HILL pseudoentropy (Håstad et al., SIAM J. Computing 1999). We show that a computational secure sketch implies an error-correcting code. Thus, HILL pseudoentropy is bounded by the size of the best error-correcting code. Similar bounds apply to information-theoretic secure sketches.

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Efficient, Reusable Fuzzy Extractors from LWE

Cited by 41 publications

References 10 publications

Fuzzy Vector Signature and Its Application to Privacy-Preserving Authentication

Fuzzy Vector Signature and Its Application to Privacy-Preserving Authentication

Reusable Fuzzy Extractors for Low-Entropy Distributions

Computational fuzzy extractors

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