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Detail publikace
HUSA, J. SEKANINA, L.
Originální název
Evolving Cryptographic Boolean Functions with Minimal Multiplicative Complexity
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
Genetic programming, Cartesian genetic programming, cryptography, multiplicative complexity, optimization.
Autoři
HUSA, J.; SEKANINA, L.
Vydáno
3. 9. 2020
Nakladatel
IEEE Computational Intelligence Society
Místo
Los Alamitos
ISBN
978-1-7281-6929-3
Kniha
2020 IEEE Congress on Evolutionary Computation (CEC)
Strany od
1
Strany do
8
Strany počet
BibTex
@inproceedings{BUT168245, author="Jakub {Husa} and Lukáš {Sekanina}", title="Evolving Cryptographic Boolean Functions with Minimal Multiplicative Complexity", booktitle="2020 IEEE Congress on Evolutionary Computation (CEC)", year="2020", pages="1--8", publisher="IEEE Computational Intelligence Society", address="Los Alamitos", doi="10.1109/CEC48606.2020.9185517", isbn="978-1-7281-6929-3" }