Detail publikace

Comparison of Genetic Programming Methods on Design of Cryptographic Boolean Functions

HUSA, J.

Originální název

Comparison of Genetic Programming Methods on Design of Cryptographic Boolean Functions

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The ever-increasing need for information security requires a constant refinement of contemporary ciphers. One of these are stream ciphers which secure data by utilizing a pseudo-randomly generated binary sequence. Generating a cryptographically secure sequence is not an easy task and requires a Boolean function possessing multiple cryptographic properties. One of the most successful ways of designing these functions is genetic programming. In this paper, we present a comparative study of three genetic programming methods, tree-based, Cartesian and linear, on the task of generating Boolean functions with an even number of inputs possessing good values of nonlinearity, balancedness, correlation immunity, and algebraic degree. Our results provide a comprehensive overview of how genetic programming methods compare when designing functions of different sizes, and we show that linear genetic programming, which has not been used for design of some of these functions before, is the best at dealing with increasing number of inputs, and creates desired functions with better reliability than the commonly used methods.

Klíčová slova

Genetic Programming, Cartesian Genetic Programming, Linear Genetic Programming, Cryptographic Boolean functions, Comparative Study.

Autoři

HUSA, J.

Vydáno

24. 4. 2019

Nakladatel

Springer International Publishing

Místo

Cham

ISBN

978-3-030-14811-9

Kniha

Genetic Programming 22st European Conference, EuroGP 2019, Proceedings

Strany od

228

Strany do

244

Strany počet

17

URL

https://www.fit.vut.cz/research/publication/11918/

BibTex

@inproceedings{BUT157181,
  author="Jakub {Husa}",
  title="Comparison of Genetic Programming Methods on Design of Cryptographic Boolean Functions",
  booktitle="Genetic Programming 22st European Conference, EuroGP 2019, Proceedings",
  year="2019",
  pages="228--244",
  publisher="Springer International Publishing",
  address="Cham",
  doi="10.1007/978-3-030-16670-0\{_}15",
  isbn="978-3-030-14811-9",
  url="https://www.fit.vut.cz/research/publication/11918/"
}