Description
We provide formal definitions and efficient secure techniques for - turning biometric and other noisy data into keys usable for *any* cryptographic application, and - reliably and securely authenticating biometric data. Our techniques apply not just to biometric information, but to any keying material that, unlike traditional cryptographic keys, is (1) not reproducible precisely and (2) not distributed uniformly. We propose two new primitives. A *fuzzy extractor* extracts nearly uniform randomness R from its biometric input; the extraction is error-tolerant in the sense that R will be the same even if the input changes, as long as it remains reasonably close to the original. Thus, R can be used as a key in any cryptographic application. A *secure sketch* produces public information about its biometric input w that does not reveal w, and yet allows exact recovery of w given another value that is close to w. Thus, it can be used to reliably reproduce error-prone biometric inputs without incurring the security risk inherent in storing them.<br/> In addition to formally introducing our new primitives, we provide nearly optimal constructions of both primitives for various measures of "closeness" of input data, such as Hamming distance, edit metric, permutation distance and set difference.
Prochains exposés
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SoK: Security of the Ascon Modes
Orateur : Charlotte Lefevre - Radboud University
The Ascon authenticated encryption scheme and hash function of Dobraunig et al (Journal of Cryptology 2021) were recently selected as winner of the NIST lightweight cryptography competition. The mode underlying Ascon authenticated encryption (Ascon-AE) resembles ideas of SpongeWrap, but not quite, and various works have investigated the generic security of Ascon-AE, all covering different attack[…] -
Comprehensive Modelling of Power Noise via Gaussian Processes with Applications to True Random Number Generators
Orateur : Maciej Skorski - Laboratoire Hubert Curien
The talk examines power noise modelling through Gaussian Processes for secure True Random Number Generators. While revisiting one-sided fractional Brownian motion, we obtain novel contributions by quantifying posterior uncertainty in exact analytical form, establishing quasi-stationary properties, and developing rigorous time-frequency analysis. These results are applied to model oscillator[…]-
Cryptography
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TRNG
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CryptoVerif: a computationally-sound security protocol verifier
Orateur : Bruno Blanchet - Inria
CryptoVerif is a security protocol verifier sound in the computational model of cryptography. It produces proofs by sequences of games, like those done manually by cryptographers. It has an automatic proof strategy and can also be guided by the user. It provides a generic method for specifying security assumptions on many cryptographic primitives, and can prove secrecy, authentication, and[…]-
Cryptography
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