Evolving constructions for balanced, highly nonlinear boolean functions
Claude Carlet, Marko Djurasevic, Domagoj Jakobović, Luca Mariot, Stjepan Picek · Proceedings of the Genetic and Evolutionary Computation Conference · 2022
Finding balanced, highly nonlinear Boolean functions is a difficult problem where it is not known what nonlinearity values are possible to be reached in general. At the same time, evolutionary computation is successfully used to evolve specific Boolean function instances, but the approach cannot easily scale for larger Boolean function sizes. Indeed, while evolving smaller Boolean functions is almost trivial, larger sizes become increasingly difficult, and evolutionary algorithms perform suboptimally.