Detail publikačního výsledku

Semantic Mutation Operator for Fast and Efficient Design of Bent Boolean Functions

HUSA, J.; SEKANINA, L.

Original Title

Semantic Mutation Operator for Fast and Efficient Design of Bent Boolean Functions

English Title

Semantic Mutation Operator for Fast and Efficient Design of Bent Boolean Functions

Type

Abstract

Original Abstract

Bent functions are a type of Boolean functions with properties that make them useful in cryptography. In this paper we propose a new semantic mutation operator for design of bent Boolean functions via genetic programming. To assess the efficiency of the proposed operator, we compare it to several other commonly used non-semantic mutation operators. Our results show that semantic mutation makes the evolutionary process more efficient, and significantly decreases the number of fitness function evaluations required to find a bent function. 

English abstract

Bent functions are a type of Boolean functions with properties that make them useful in cryptography. In this paper we propose a new semantic mutation operator for design of bent Boolean functions via genetic programming. To assess the efficiency of the proposed operator, we compare it to several other commonly used non-semantic mutation operators. Our results show that semantic mutation makes the evolutionary process more efficient, and significantly decreases the number of fitness function evaluations required to find a bent function. 

Keywords

Genetic Programming, Semantic Mutation, Bent Boolean Functions.

Key words in English

Genetic Programming, Semantic Mutation, Bent Boolean Functions.

Authors

HUSA, J.; SEKANINA, L.

Released

12.04.2023

Location

Brno

Book

Evo* 2023 -- Late-Breaking Abstracts Volume

Pages count

4

URL

https://www.fit.vut.cz/research/publication/12983/

Full text in the Digital Library

http://hdl.handle.net/

BibTex

@misc{BUT186710,
  author="Jakub {Husa} and Lukáš {Sekanina}",
  title="Semantic Mutation Operator for Fast and Efficient Design of Bent Boolean Functions",
  booktitle="Evo* 2023 -- Late-Breaking Abstracts Volume",
  year="2023",
  pages="4",
  address="Brno",
  url="https://www.fit.vut.cz/research/publication/12983/",
  note="Abstract"
}

Documents

extended-abstract