Abstract: In this contribution instances of a problem introduced by the differential cryptanalysis of Feistel cryptosystems are formulated as optimization tasks. The performance of EvolutionaryComputation methods on these tasks is studied for a representative Feistel cryptosystem, the Data Encryption Standard. The results indicate that the proposed methodology is efficient in handling this type of problems and furthermore, that its effectiveness depends mainly on the construction of the objective function. This approach is applicable to all Feistel cryptosystems that are amenable to differential cryptanalysis.
Abstract: Evolutionary Game Theory is the study of strategic interactions among large populations of agents who base their decisions on simple, myopic rules. A major goal of the theory is to determine broad classes of decision procedures which both provide plausible descriptions of selfish behaviour and include appealing forms of aggregate behaviour. For example, properties such as the correlation between strategies' growth rates and payoffs, the connection between stationary states and Nash equilibria and global guarantees of convergence to equilibrium, are widely studied in the literature. In this paper we discuss some computational aspects of the theory, which we prefer to view more as Game Theoretic Aspects of Evolution than Evolutionary Game Theory, since the term "evolution" actually refers to strategic adaptation of individuals ' behaviour through a dynamic process and not the traditional evolution of populations. We consider this dynamic process as a self-organization procedure, which under certain conditions leads to some kind of stability and assures robustness against invasion.