Evolutionary Construction of Perfectly Balanced Boolean Functions
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{Mariot:2022:CEC,
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author = "Luca Mariot and Stjepan Picek and
Domagoj Jakobovic and Marko Djurasevic and Alberto Leporati",
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booktitle = "2022 IEEE Congress on Evolutionary Computation (CEC)",
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title = "Evolutionary Construction of Perfectly Balanced
Boolean Functions",
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year = "2022",
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editor = "Carlos A. Coello Coello and Sanaz Mostaghim",
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address = "Padua, Italy",
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month = "18-23 " # jul,
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isbn13 = "978-1-6654-6708-7",
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abstract = "Finding Boolean functions suitable for cryptographic
primitives is a complex combinatorial optimization
problem, since they must satisfy several properties to
resist crypt-analytic attacks, and the space is very
large, which grows super exponentially with the number
of input variables. Recent research has focused on the
study of Boolean functions that satisfy properties on
restricted sets of inputs due to their importance in
the development of the FLIP stream cipher. In this
paper, we consider one such property, perfect
balancedness, and investigate the use of Genetic
Programming (GP) and Genetic Algorithms (GA) to
construct Boolean functions that satisfy this property
along with a good nonlinearity profile. We formulate
the related optimization problem and define two
encodings for the candidate solutions, namely the truth
table and the weight wise balanced representations.
Somewhat surprisingly, the results show that GA with
the weightwise balanced representation outperforms GP
with the classical truth table phenotype in finding
highly nonlinear Weightwise Perfectly Balanced (WPB)
functions. This is in stark contrast to previous
findings on the evolution of balanced Boolean
functions, where GP always performs best.",
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keywords = "genetic algorithms, genetic programming, Ciphers,
Boolean functions, Input variables, Resists,
Evolutionary computation, Boolean functions,
balancedness, nonlinearity",
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DOI = "doi:10.1109/CEC55065.2022.9870427",
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notes = "Also known as \cite{9870427}",
- }
Genetic Programming entries for
Luca Mariot
Stjepan Picek
Domagoj Jakobovic
Marko Durasevic
Alberto Leporati
Citations