Publication Details

Evolving Cryptographic Boolean Functions with Minimal Multiplicative Complexity

HUSA Jakub and SEKANINA Lukáš. Evolving Cryptographic Boolean Functions with Minimal Multiplicative Complexity. In: 2020 IEEE Congress on Evolutionary Computation (CEC). Los Alamitos: IEEE Computational Intelligence Society, 2020, pp. 1-8. ISBN 978-1-7281-6929-3.
Czech title
Evoluce Kryptografických Booleovských funkcí s Minimální Násobkovou Složitostí
Type
conference paper
Language
english
Authors
Keywords

Genetic programming, Cartesian genetic programming, cryptography, multiplicative complexity, optimization.

Abstract

The multiplicative complexity (MC) is a cryptographic criterion that describes the vulnerability of a Boolean function to certain algebraic attacks, and in many important cryptographic applications also determines the computational cost. In this paper, we use Cartesian genetic programming to find various types of cryptographic Boolean functions, improve their implementation to achieve the minimal MC, and examine how difficult these optimized functions are to find in comparison to functions than only need to satisfy some base cryptographic criteria. To provide a comparison with other state-of-the-art optimization approaches, we also use our method to improve the implementation of several generic benchmark circuits. Our results provide new upper limits on MC of certain functions, show that our approach is competitive, and also that finding functions with an implementation that has better MC is not mutually exclusive with improving other performance criteria.

Published
2020
Pages
1-8
Proceedings
2020 IEEE Congress on Evolutionary Computation (CEC)
Conference
IEEE Congress on Evolutionary Computation, Glasgow, GB
ISBN
978-1-7281-6929-3
Publisher
IEEE Computational Intelligence Society
Place
Los Alamitos, US
DOI
UT WoS
000703998200029
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB12190,
   author = "Jakub Husa and Luk\'{a}\v{s} Sekanina",
   title = "Evolving Cryptographic Boolean Functions with Minimal Multiplicative Complexity",
   pages = "1--8",
   booktitle = "2020 IEEE Congress on Evolutionary Computation (CEC)",
   year = 2020,
   location = "Los Alamitos, US",
   publisher = "IEEE Computational Intelligence Society",
   ISBN = "978-1-7281-6929-3",
   doi = "10.1109/CEC48606.2020.9185517",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12190"
}
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