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A genetic algorithmic approach to the differential and linear cryptanalysis
The two most well known and recently developed methods in cryptanalysis of DES and DES-like symmetric block ciphers are difTerential and linear cryptanalysis. But these cryptanalytic attacks need to be improved due to the computational performance and storage capacity problems On the other hand, genetic algorithms can be a good solution in cases where the optimum value or near-optimum solutions are sought in complex systems or for non-linear problems. This is a valid situation for the cryptanalysis case where DES and DES-like ciphers are non-linear in structure making dilTerential and linear cryptanalysis a complex system with a very large search landscape and extreme amount of conditional and probabilistic candidates for the key being sought. In this study, a new and promising method wit h bet ter performance is to be developed for differential/linear cryptanalysis of DES and similar symmetric cryptosystems exploiting genetic algorithms' broadened search and optimum finding capacity.