Evolutionary Approach to S-box Generation: Optimizing Nonlinear Substitutions in Symmetric Ciphers

Fuente: arXiv
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Main Authors: Kuznetsov, Oleksandr, Poluyanenko, Nikolay, Frontoni, Emanuele, Arnesano, Marco, Smirnov, Oleksii
Format: Preprint
Published: 2024
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author Kuznetsov, Oleksandr
Poluyanenko, Nikolay
Frontoni, Emanuele
Arnesano, Marco
Smirnov, Oleksii
author_facet Kuznetsov, Oleksandr
Poluyanenko, Nikolay
Frontoni, Emanuele
Arnesano, Marco
Smirnov, Oleksii
contents This study explores the application of genetic algorithms in generating highly nonlinear substitution boxes (S-boxes) for symmetric key cryptography. We present a novel implementation that combines a genetic algorithm with the Walsh-Hadamard Spectrum (WHS) cost function to produce 8x8 S-boxes with a nonlinearity of 104. Our approach achieves performance parity with the best-known methods, requiring an average of 49,399 iterations with a 100% success rate. The study demonstrates significant improvements over earlier genetic algorithm implementations in this field, reducing iteration counts by orders of magnitude. By achieving equivalent performance through a different algorithmic approach, our work expands the toolkit available to cryptographers and highlights the potential of genetic methods in cryptographic primitive generation. The adaptability and parallelization potential of genetic algorithms suggest promising avenues for future research in S-box generation, potentially leading to more robust, efficient, and innovative cryptographic systems. Our findings contribute to the ongoing evolution of symmetric key cryptography, offering new perspectives on optimizing critical components of secure communication systems.
format Preprint
id arxiv_https___arxiv_org_abs_2407_03510
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Evolutionary Approach to S-box Generation: Optimizing Nonlinear Substitutions in Symmetric Ciphers
Kuznetsov, Oleksandr
Poluyanenko, Nikolay
Frontoni, Emanuele
Arnesano, Marco
Smirnov, Oleksii
Cryptography and Security
This study explores the application of genetic algorithms in generating highly nonlinear substitution boxes (S-boxes) for symmetric key cryptography. We present a novel implementation that combines a genetic algorithm with the Walsh-Hadamard Spectrum (WHS) cost function to produce 8x8 S-boxes with a nonlinearity of 104. Our approach achieves performance parity with the best-known methods, requiring an average of 49,399 iterations with a 100% success rate. The study demonstrates significant improvements over earlier genetic algorithm implementations in this field, reducing iteration counts by orders of magnitude. By achieving equivalent performance through a different algorithmic approach, our work expands the toolkit available to cryptographers and highlights the potential of genetic methods in cryptographic primitive generation. The adaptability and parallelization potential of genetic algorithms suggest promising avenues for future research in S-box generation, potentially leading to more robust, efficient, and innovative cryptographic systems. Our findings contribute to the ongoing evolution of symmetric key cryptography, offering new perspectives on optimizing critical components of secure communication systems.
title Evolutionary Approach to S-box Generation: Optimizing Nonlinear Substitutions in Symmetric Ciphers
topic Cryptography and Security
url https://arxiv.org/abs/2407.03510