Bent Function Synthesis by Means of Cartesian Genetic Programming

In this paper, a new approach to synthesize bent Boolean functions by means of Cartesian Genetic Programming (CGP) is proposed. Bent functions have important applications in cryptography due to their high nonlinearity. However, they are very rare and their discovery using conventional brute force methods is not efficient enough. We show that by using CGP we can routinely design bent functions of up to 16 variables. The evolutionary approach exploits parallelism in both the fitness calculation and the search algorithm.

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