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Optimization of a Simulated Annealing Algorithm for S-Boxes Generating
Cryptographic algorithms are used to ensure confidentiality, integrity and authenticity of data in information systems. One of the important areas of modern cryptography is that of symmetric key ciphers. They convert the input plaintext into ciphertext, representing it as a random sequence of charac...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9415565/ https://www.ncbi.nlm.nih.gov/pubmed/36015833 http://dx.doi.org/10.3390/s22166073 |
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author | Kuznetsov, Alexandr Wieclaw, Lukasz Poluyanenko, Nikolay Hamera, Lukasz Kandiy, Sergey Lohachova, Yelyzaveta |
author_facet | Kuznetsov, Alexandr Wieclaw, Lukasz Poluyanenko, Nikolay Hamera, Lukasz Kandiy, Sergey Lohachova, Yelyzaveta |
author_sort | Kuznetsov, Alexandr |
collection | PubMed |
description | Cryptographic algorithms are used to ensure confidentiality, integrity and authenticity of data in information systems. One of the important areas of modern cryptography is that of symmetric key ciphers. They convert the input plaintext into ciphertext, representing it as a random sequence of characters. S-boxes are designed to complicate the input–output relationship of the cipher. In other words, S-boxes introduce nonlinearity into the encryption process, complicating the use of different methods of cryptanalysis (linear, differential, statistical, correlation, etc.). In addition, S-boxes must be random. This property means that nonlinear substitution cannot be represented as simple algebraic constructions. Random S-boxes are designed to protect against algebraic methods of cryptanalysis. Thus, generation of random S-boxes is an important area of research directly related to the design of modern cryptographically strong symmetric ciphers. This problem has been solved in many related works, including some using the simulated annealing (SA) algorithm. Some works managed to generate 8-bit bijective S-boxes with a nonlinearity index of 104. However, this required enormous computational resources. This paper presents the results of our optimization of SA via various parameters. We were able to significantly reduce the computational complexity of substitution generation with SA. In addition, we also significantly increased the probability of generating the target S-boxes with a nonlinearity score of 104. |
format | Online Article Text |
id | pubmed-9415565 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94155652022-08-27 Optimization of a Simulated Annealing Algorithm for S-Boxes Generating Kuznetsov, Alexandr Wieclaw, Lukasz Poluyanenko, Nikolay Hamera, Lukasz Kandiy, Sergey Lohachova, Yelyzaveta Sensors (Basel) Article Cryptographic algorithms are used to ensure confidentiality, integrity and authenticity of data in information systems. One of the important areas of modern cryptography is that of symmetric key ciphers. They convert the input plaintext into ciphertext, representing it as a random sequence of characters. S-boxes are designed to complicate the input–output relationship of the cipher. In other words, S-boxes introduce nonlinearity into the encryption process, complicating the use of different methods of cryptanalysis (linear, differential, statistical, correlation, etc.). In addition, S-boxes must be random. This property means that nonlinear substitution cannot be represented as simple algebraic constructions. Random S-boxes are designed to protect against algebraic methods of cryptanalysis. Thus, generation of random S-boxes is an important area of research directly related to the design of modern cryptographically strong symmetric ciphers. This problem has been solved in many related works, including some using the simulated annealing (SA) algorithm. Some works managed to generate 8-bit bijective S-boxes with a nonlinearity index of 104. However, this required enormous computational resources. This paper presents the results of our optimization of SA via various parameters. We were able to significantly reduce the computational complexity of substitution generation with SA. In addition, we also significantly increased the probability of generating the target S-boxes with a nonlinearity score of 104. MDPI 2022-08-14 /pmc/articles/PMC9415565/ /pubmed/36015833 http://dx.doi.org/10.3390/s22166073 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kuznetsov, Alexandr Wieclaw, Lukasz Poluyanenko, Nikolay Hamera, Lukasz Kandiy, Sergey Lohachova, Yelyzaveta Optimization of a Simulated Annealing Algorithm for S-Boxes Generating |
title | Optimization of a Simulated Annealing Algorithm for S-Boxes Generating |
title_full | Optimization of a Simulated Annealing Algorithm for S-Boxes Generating |
title_fullStr | Optimization of a Simulated Annealing Algorithm for S-Boxes Generating |
title_full_unstemmed | Optimization of a Simulated Annealing Algorithm for S-Boxes Generating |
title_short | Optimization of a Simulated Annealing Algorithm for S-Boxes Generating |
title_sort | optimization of a simulated annealing algorithm for s-boxes generating |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9415565/ https://www.ncbi.nlm.nih.gov/pubmed/36015833 http://dx.doi.org/10.3390/s22166073 |
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