Secret réparti

Résumé

Le secret réparti ou le partage de secret consiste à distribuer un secret, par exemple une clé ou un mot de passe, entre plusieurs dépositaires. Le secret ne peut être découvert que si un nombre suffisant de dépositaires mettent en commun les informations qu'ils ont reçues. En revanche, un nombre inférieur de dépositaire n’apporte aucune information sur le secret. Le secret réparti a été inventé indépendamment par Adi Shamir et George Blakley en 1979. Principe Plus formellement, n dépositaires reçoivent chacun une information différente. Si un groupe quelconque de t dépositaires parmi les n dépositaires mettent en commun leurs informations, ils retrouvent la donnée secrète. En revanche, un groupe de moins de t dépositaires ne doit rien pouvoir apprendre de la donnée secrète avec les informations dont ils disposent. Xor Si n=t, c'est-à-dire si tous les dépositaires doivent être nécessaires pour retrouver la donnée secrète, la méthode la plus simpl

Source officielle

https://fr.wikipedia.org/wiki/Secret_r%C3%A9parti

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Publications associées (17)

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Concepts associés (5)

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Cours associés (5)

A decentralized system is one that works when no single party is in charge or fully trusted. This course teaches decentralized systems principles while guiding students through the development and testing of their own decentralized system incorporating messaging, encryption, and blockchain concepts.

This course provides an overview of information security and privacy topics. It introduces students to the knowledge and tools they will need to deal with the security/privacy challenges they are likely to encounter in today's Big Data world. The tools are illustrated with relevant applications.

Information-theoretic methods and their application to secrecy & privacy. Perfect information-theoretic secrecy. Randomness extraction & privacy amplification. Secret key generation from common randomness. Measures of information leakage incl. differential privacy, perfect privacy, & mutual info.

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Séances de cours associées (13)

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In this paper, we evaluate the performances of state-of-the art higher-order masking schemes for the AES. Doing so, we pay a particular attention to the comparison between specialized solutions introduced exclusively as countermeasures against side-channel analysis, and a recent proposal by Roche and Prouff exploiting MultiParty Computation (MPC) techniques. We show that the additional security features this latter scheme provides (e.g. its glitch-freeness) comes at the cost of large performance overheads.We then study how exploiting standard optimization techniques from the MPC literature can be used to reduce this gap. In particular, we show that “packed secret sharing” based on a modified multiplication algorithm can speed up MPC-based masking when the order of the masking scheme increases. Eventually, we discuss the randomness requirements of masked implementations. For this purpose, we first show with information theoretic arguments that the security guarantees of masking are only preserved if this randomness is uniform, and analyze the consequences of a deviation from this requirement. We then conclude the paper by including the cost of randomness generation in our performance evaluations. These results should help actual designers to choose a masking scheme based on security and performance constraints.

2013

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Secure numerical and logical multi party operations

Bin Lu

We derive algorithms for efficient secure numerical and logical operations in the semi-honest model ensuring statistical or perfect security for secure multi-party computation (MPC). To derive our algorithms for trigonometric functions, we use basic mathematical laws in combination with properties of the additive encryption scheme, ie. linear secret sharing, in a novel way for the JOS scheme [23]. For division and logarithm, we use a new approach to compute a Taylor series at a fixed point for all numbers. Our empirical evaluation yields speed-ups for local computation of more than a factor of 100 for some operations compared to the state-of-the-art. (C) 2017 Elsevier Ltd. All rights reserved.

Elsevier Science Bv2017

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Scalable Bias-Resistant Distributed Randomness

Bryan Alexander Ford, Nicolas Gailly, Linus Gasser, Philipp Svetolik Jovanovic, Ismail Khoffi, Eleftherios Kokoris Kogias

Bias-resistant public randomness is a critical component in many (distributed) protocols. Existing solutions do not scale to hundreds or thousands of participants, as is needed in many decentralized systems. We propose two large-scale distributed protocols, RandHound and RandHerd, which provide publicly-verifiable, unpredictable, and unbiasable randomness against Byzantine adversaries. RandHound relies on an untrusted client to divide a set of randomness servers into groups for scalability, and it depends on the pigeonhole principle to ensure output integrity, even for non-random, adversarial group choices. RandHerd implements an efficient, decentralized randomness beacon. RandHerd is structurally similar to a BFT protocol, but uses RandHound in a one-time setup to arrange participants into verifiably unbiased random secret-sharing groups, which then repeatedly produce random output at predefined intervals. Our prototype demonstrates that RandHound and RandHerd achieve good performance across hundreds of participants while retaining a low failure probability by properly selecting protocol parameters, such as a group size and secret-sharing threshold. For example, when sharding 512 nodes into groups of 32, our experiments show that RandHound can produce fresh random output after 240 seconds. RandHerd, after a setup phase of 260 seconds, is able to generate fresh random output in intervals of approximately 6 seconds. For this configuration, both protocols operate at a failure probability of at most 0.08% against a Byzantine adversary.

Ieee2017

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