Detail publikačního výsledku

Evolving Cryptographic Boolean Functions with Minimal Multiplicative Complexity

HUSA, J.; SEKANINA, L.

Originální název

Evolving Cryptographic Boolean Functions with Minimal Multiplicative Complexity

Anglický název

Evolving Cryptographic Boolean Functions with Minimal Multiplicative Complexity

Druh

Stať ve sborníku v databázi WoS či Scopus

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.

Anglický 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.

Klíčová slova v angličtině

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

Autoři

HUSA, J.; SEKANINA, L.

Rok RIV

2021

Vydáno

03.09.2020

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

8

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"
}