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On Counts and Densities of Homogeneous Bent Functions: An Evolutionary Approach

Published: November 16, 2025 | arXiv ID: 2511.12652v1

By: Claude Carlet , Marko Ðurasevic , Domagoj Jakobovic and more

Potential Business Impact:

Finds secret codes that are super hard to break.

Business Areas:
Bioinformatics Biotechnology, Data and Analytics, Science and Engineering

Boolean functions with strong cryptographic properties, such as high nonlinearity and algebraic degree, are important for the security of stream and block ciphers. These functions can be designed using algebraic constructions or metaheuristics. This paper examines the use of Evolutionary Algorithms (EAs) to evolve homogeneous bent Boolean functions, that is, functions whose algebraic normal form contains only monomials of the same degree and that are maximally nonlinear. We introduce the notion of density of homogeneous bent functions, facilitating the algorithmic design that results in finding quadratic and cubic bent functions in different numbers of variables.

Country of Origin
🇳🇱 Netherlands

Page Count
18 pages

Category
Computer Science:
Neural and Evolutionary Computing