In this paper we present the results on applying evolutionary computation techniques to construction of several cryptographic attacks. In particular, SAT-based guess-and-determine attacks studied in the context of algebraic cryptanalysis. Each of these attacks is built upon some set of Boolean variables, thus it can be specified by a Boolean vector. We use two general evolutionary strategies to find an optimal vector: (1+1)-EA and GA. Based on these strategies parallel algorithms (based on modern SAT-solvers) for solving the problem of minimization of a special pseudo-Boolean function are implemented. This function is a fitness function used to evaluate the runtime of a guess-and-determine attack. We compare the efficiency of (1+1)-EA and GA with the algorithm from the Tabu search class, that was earlier used to solve related problems. Our GA-based solution showed the best results on a number of test instances, namely, cryptanalysis problems of several stream ciphers (cryptographic keystream generators).
CITATION STYLE
Pavlenko, A., Semenov, A., & Ulyantsev, V. (2019). Evolutionary computation techniques for constructing SAT-based attacks in algebraic cryptanalysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11454 LNCS, pp. 237–253). Springer Verlag. https://doi.org/10.1007/978-3-030-16692-2_16
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