Detail publikačního výsledku

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

HUSA, J.; SEKANINA, L.

Originální název

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

Anglický název

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

Druh

Abstrakt

Originální abstrakt

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. 

Anglický abstrakt

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. 

Klíčová slova

Genetic Programming, Semantic Mutation, Bent Boolean Functions.

Klíčová slova v angličtině

Genetic Programming, Semantic Mutation, Bent Boolean Functions.

Autoři

HUSA, J.; SEKANINA, L.

Vydáno

12.04.2023

Místo

Brno

Kniha

Evo* 2023 -- Late-Breaking Abstracts Volume

Strany počet

4

URL

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

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"
}

Dokumenty

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