Fonction de hachage

Résumé

Quand il s'agit de mettre dans un tableau de taille raisonnable (typiquement résidant dans la mémoire principale de l'ordinateur) un ensemble de données de taille variable et arbitraire, on utilise une fonction de hachage pour attribuer à ces données des indices de ce tableau. Par conséquent, une fonction de hachage est une fonction qui associe des valeurs de taille fixe à des données de taille quelconque. Les valeurs renvoyées par une fonction de hachage sont appelées valeurs de hachage, codes de hachage, résumés, signatures ou simplement hachages. Les valeurs sont généralement utilisées pour être les indices d'une table de taille raisonnable appelée table de hachage. Le hachage ou adressage de stockage dispersé est donc l'utilisation d'une fonction de hachage pour créer les indices d'une table de hachage. Les fonctions de hachage sont utilisées dans les applications de stockage et d'indexation de données pour accéder aux données en un temps réduit, en fait quasi-constant. Elles re

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https://fr.wikipedia.org/wiki/Fonction_de_hachage

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Interpreting Hash Function Security Proofs

Juraj Sarinay

We provide a concrete security treatment of several "provably secure" hash functions. Interpreting arguments behind MQ-HASH, FSB, SWIFFTX and VSH we identify similar lines of reasoning. We aim to formulate the main security claims in a language closer to that of attacks. We evaluate designers' claims of provable security and quantify them more precisely, deriving "second order" bounds on bounds. While the authors of FSB, MQ-HASH and SWIFFT(X) prove existence of non-trivial lower bounds on security, we show that the quantification of the bounds limits the practical significance of the proofs.

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2010

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Faster and Smoother - VSH Revisited

Juraj Sarinay

We reconsider the provably collision resistant Very Smooth Hash and propose a small change in the design aiming to improve both performance and security. While the original proofs of security based on hardness of factoring or discrete logarithms are preserved, we can base the security on the k-sum problem studied by Wagner and more recently by Minder Sz. Sinclair. The new approach allows to output shorter digests and brings the speed of Fast VSH closer to the range of "classical" hash functions. The modified VSH is likely to remain secure even if factoring and discrete logarithms are easy, while this would have a devastating effect on the original versions. This observation leads us to propose a variant that operates modulo a power of two to increase the speed even more. A function that offers an equivalent of 128-bit collision resistance runs at 68.5 MB/s on a 2.4 CHz Intel Core 2 CPU, more than a third of the speed of SH A-256.

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2011

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We consider several "provably secure" hash functions that compute simple sums in a well chosen group (G,*). Security properties of such functions provably translate in a natural way to computational problems in G that are simple to define and possibly also hard to solve. Given k disjoint lists Li of group elements, the k-sum problem asks for gi ∊ Li such that g1 * g2 ... gk = 1G. Hardness of the problem in the respective groups follows from some "standard" assumptions used in public-key cryptology such as hardness of integer factoring, discrete logarithms, lattice reduction and syndrome decoding. We point out evidence that the k-sum problem may even be harder than the above problems. Two hash functions based on the group k-sum problem, SWIFFTX and FSB, were submitted to NIST as candidates for the future SHA-3 standard. Both submissions were supported by some sort of a security proof. We show that the assessment of security levels provided in the proposals is not related to the proofs included. The main claims on security are supported exclusively by considerations about available attacks. By introducing "second-order" bounds on bounds on security, we expose the limits of such an approach to provable security. A problem with the way security is quantified does not necessarily mean a problem with security itself. Although FSB does have a history of failures, recent versions of the two above functions have resisted cryptanalytic efforts well. This evidence, as well as the several connections to more standard problems, suggests that the k-sum problem in some groups may be considered hard on its own, and possibly lead to provable bounds on security. Complexity of the non-trivial tree algorithm is becoming a standard tool for measuring the associated hardness. We propose modifications to the multiplicative Very Smooth Hash and derive security from multiplicative k-sums in contrast to the original reductions that related to factoring or discrete logarithms. Although the original reductions remain valid, we measure security in a new, more aggressive way. This allows us to relax the parameters and hash faster. We obtain a function that is only three times slower compared to SHA-256 and is estimated to offer at least equivalent collision resistance. The speed can be doubled by the use of a special modulus, such a modified function is supported exclusively by the hardness of multiplicative k-sums modulo a power of two. Our efforts culminate in a new multiplicative k-sum function in finite fields that further generalizes the design of Very Smooth Hash. In contrast to the previous variants, the memory requirements of the new function are negligible. The fastest instance of the function expected to offer 128-bit collision resistance runs at 24 cycles per byte on an Intel Core i7 processor and approaches the 17.4 figure of SHA-256. The new functions proposed in this thesis do not provably achieve a usual security property such as preimage or collision resistance from a well-established assumption. They do however enjoy unconditional provable separation of inputs that collide. Changes in input that are small with respect to a well defined measure never lead to identical output in the compression function.

EPFL2011

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EPFL2011