Propositional satisfiability (SAT) is at the nucleus of state-of-the-art approaches to a variety of computationally hard problems, one of which is cryptanalysis. Moreover, a number of practical applications of SAT can only be tackled efficiently by identifying and exploiting a subset of formula's variables called backdoor set (or simply backdoors). This paper proposes a new class of backdoor sets for SAT used in the context of cryptographic attacks, namely guess-and-determine attacks. The idea is to identify the best set of backdoor variables subject to a statistically estimated hardness of the guess-and-determine attack using a SAT solver. Experimental results on weakened variants of the renowned encryption algorithms exhibit advantage of the proposed approach compared to the state of the art in terms of the estimated hardness of the resulting guess-and-determine attacks.

In this paper we study the inversion problem of MD4 cryptographic hash function developed by R. Rivest in 1990. By MD4-k we denote a truncated variant of MD4 hash function in which k represents a number of steps used to calculate a hash value (the full version of MD4 function corresponds to MD4-48). H. Dobbertin has showed that MD4-32 hash function is not one-way, namely, it can be inverted for the given image of a random input. He suggested to add special conditions to the equations that describe the computation of concrete steps (chaining variables) of the considered hash function. These additional conditions allowed to solve the inversion problem of MD4-32 within a reasonable time by solving corresponding system of equations. The main result of the present paper is an automatic derivation of "Dobbertin's conditions" using parallel SAT solving algorithms. We also managed to solve several inversion problems of functions of the kind MD4-k (for k from 31 up to 39 inclusive). Our method significantly outperforms previously existing approaches to solving these problems.

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In this paper we present the Transalg system, designed to produce SAT encodings for discrete functions, written as programs in a specific language. Translation of such programs to SAT is based on propositional encoding methods for formal computing models and on the concept of symbolic execution. We used the Transalg system to make SAT encodings for a number of cryptographic functions.

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