Towards cryptographic function distinguishers with evolutionary circuits

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Publikace nespadá pod Ekonomicko-správní fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
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ŠVENDA Petr UKROP Martin MATYÁŠ Václav

Rok publikování 2013
Druh Článek ve sborníku
Konference Proceedings of SECRYPT 2013, 10th International Conference on Security and Cryptography
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www SeCrypt 2013 supplementary data
Obor Informatika
Klíčová slova eStream; genetic programming; random distinguisher; randomness statistical testing; software circuit
Popis Cryptanalysis of a cryptographic function usually requires advanced cryptanalytical skills and extensive amount of human labour. However, some automation is possible, e.g., by using randomness testing suites like STS NIST or Dieharder. These can be applied to test statistical properties of cryptographic function outputs. Yet such testing suites are limited only to predefined patterns testing particular statistical defects. We propose more open approach based on a combination of software circuits and evolutionary algorithms to search for unwanted statistical properties like next bit predictability, random data non-distinguishability or strict avalanche criterion. Software circuit that acts as a testing function is automatically evolved by a stochastic optimization algorithm and uses information leaked during cryptographic function evaluation. We tested this general approach on problem of finding a distinguisher of outputs produced by several candidate algorithms for eStream competition from truly random sequences. We obtained similar results (with some exceptions) as those produced by STS NIST and Dieharder tests w.r.t. the number of rounds of the inspected algorithm. This paper focuses on providing solid assessment of the proposed approach w.r.t. STS NIST and Dieharder when applied over multiple different algorithms rather than obtaining best possible result for a particular one. Additionally, proposed approach is able to provide random distinguisher even when presented with very short sequence like 16 bytes only.
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