Hyper-bent Boolean Functions and Evolutionary Algorithms
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{Mariot:2019:EuroGP,
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author = "Luca Mariot and Domagoj Jakobovic and
Alberto Leporati and Stjepan Picek",
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title = "Hyper-bent {Boolean} Functions and Evolutionary
Algorithms",
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booktitle = "EuroGP 2019: Proceedings of the 22nd European
Conference on Genetic Programming",
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year = "2019",
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month = "24-26 " # apr,
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editor = "Lukas Sekanina and Ting Hu and Nuno Lourenco",
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series = "LNCS",
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volume = "11451",
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publisher = "Springer Verlag",
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address = "Leipzig, Germany",
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pages = "262--277",
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organisation = "EvoStar, Species",
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keywords = "genetic algorithms, genetic programming, Bent
functions, Hyper-bent functions, Evolution strategies:
Poster",
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isbn13 = "978-3-030-16669-4",
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URL = "https://www.springer.com/us/book/9783030166694",
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DOI = "doi:10.1007/978-3-030-16670-0_17",
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size = "16 pages",
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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.",
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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