An External Parameter Independent Novel Cost Function for Evolving Bijective Substitution-Boxes

摘要: The property of nonlinearity has high importance for the design strong substitution boxes. Therefore, development new techniques to produce boxes with values is essential. Many research papers have shown that optimization algorithms are an efficient technique obtain good solutions. However, there no reference in public literature showing a heuristic method obtains optimal unless seeded initial Moreover, majority best reported pseudo-random seeding algorithm(s) often achieve their results help some cost function(s) over Walsh–Hadamard spectrum substitution. In sense, we proposed present, this paper, novel external parameter independent function evolving bijective s-boxes nonlinearity, which highly correlated property. Several approaches including GaT (genetic and tree), LSA (local search algorithm), Hill Climbing algorithm been investigated assess performance evolved s-boxes. A comparison done show advantages our function, respect functions like Clark’s Picek’s functions.