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A new approach of known plaintext attack with Genetic Algorithm

机译:具有遗传算法的已知明文攻击的新方法

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Cryptanalysis of modern cryptosystems is viewed as NP-Hard problem. Block ciphers, a modern symmetric key cipher are characterised with the nonlinearity and low autocorrelation of their structure. In literature, various attacks were accomplished based on traditional research algorithms such the brute force, but results still insufficient especially with wide instances due to resources requirement, which increase with the size of the problem. Actual research tends toward the use of bio-inspired intelligence algorithms, which are heuristic methods able to handle various combinatorial problems due to their optimisation of search space and fast convergence with reasonable resource consumption. The paper presents a new approach based on genetic algorithm for cryptanalysis of block ciphers; we focuses especially around the problem formulation, which seems a critical factor that depends the attack success. The experiments were accomplished on various set of data; the obtained results indicate that the proposed methodology seems an efficient tool in handling such attacks. Moreover, results comparisons of the considered approach with similar heuristics such Particle Swarm Optimisation and Brute Force reports its effectiveness in solving the considered problem.
机译:现代密码系统的密码分析被视为NP难题。块密码,一个现代对称密钥密码的特征在于它们结构的非线性和低自相关。在文献中,基于传统的研究算法实现了各种攻击,但由于资源要求,结果仍然不足,特别是由于资源要求而导致的范围。实际研究倾向于利用生物启发智能算法,这是能够通过优化搜索空间的优化和具有合理资源消耗的快速收敛来处理各种组合问题的启发式方法。本文提出了一种基于块密码粘附分析的遗传算法的新方法;我们特别关注问题制定,这似乎是取决于攻击成功的关键因素。实验是在各种数据上完成的;所获得的结果表明,所提出的方法似乎是处理此类攻击的有效工具。此外,结果对具有类似启发式粒子群优化和蛮力的所考虑方法的比较报告了解决所考虑的问题的有效性。

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