Hyper-bent Boolean Functions and Evolutionary Algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Mariot:2019:EuroGP,

• author = "Luca Mariot and Domagoj Jakobovic and Alberto Leporati and Stjepan Picek",
• title = "Hyper-bent {Boolean} Functions and Evolutionary Algorithms",
• booktitle = "EuroGP 2019: Proceedings of the 22nd European Conference on Genetic Programming",
• year = "2019",
• month = "24-26 " # apr,
• editor = "Lukas Sekanina and Ting Hu and Nuno Lourenco",
• series = "LNCS",
• volume = "11451",
• publisher = "Springer Verlag",
• address = "Leipzig, Germany",
• pages = "262--277",
• organisation = "EvoStar, Species",
• keywords = "genetic algorithms, genetic programming, Bent functions, Hyper-bent functions, Evolution strategies: Poster",
• isbn13 = "978-3-030-16669-4",
• URL = "https://www.springer.com/us/book/9783030166694",
• DOI = "doi:10.1007/978-3-030-16670-0_17",
• size = "16 pages",
• abstract = "Bent Boolean functions play an important role in the design of secure symmetric ciphers, since they achieve the maximum distance from affine functions allowed by Parsevals relation. Hyper-bent functions, in turn, are those bent functions which additionally reach maximum distance from all bijective monomial functions, and provide further security towards approximation attacks. Being characterized by a stricter definition, hyper-bent functions are rarer than bent functions, and much more difficult to construct. In this paper, we employ several evolutionary algorithms in order to evolve hyper-bent Boolean functions of various sizes. Our results show that hyper-bent functions are extremely difficult to evolve, since we manage to find such functions only for the smallest investigated size. Interestingly, we are able to identify this difficulty as not lying in the evolution of hyper-bent functions itself, but rather in evolving some of their components, i.e. bent functions. Finally, we present an additional parameter to evaluate the performance of evolutionary algorithms when evolving Boolean functions: the diversity of the obtained solutions.",
• notes = "http://www.evostar.org/2019/cfp_eurogp.php#abstracts Part of \cite{Sekanina:2019:GP} EuroGP'2019 held in conjunction with EvoCOP2019, EvoMusArt2019 and EvoApplications2019",

}

Genetic Programming entries for Luca Mariot Domagoj Jakobovic Alberto Leporati Stjepan Picek

Citations