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Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization

This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. Unlike most competing works (which typically integrate a single chaotic map int...

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Main Authors: Kamal Zuhairi, Zamli, Din, Fakhrud, Alhadawi, Hussam S.
Format: Article
Language:English
English
Published: Springer Science and Business Media Deutschland GmbH 2023
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://umpir.ump.edu.my/id/eprint/40759/1/Exploring%20a%20Q-learning-based%20chaotic%20naked%20mole%20rat%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/40759/2/Exploring%20a%20Q-learning-based%20chaotic%20naked%20mole%20rat%20algorithm%20for%20S-box%20construction%20and%20optimization_ABS.pdf
http://umpir.ump.edu.my/id/eprint/40759/
https://doi.org/10.1007/s00521-023-08243-3
https://doi.org/10.1007/s00521-023-08243-3
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spelling my.ump.umpir.407592024-05-28T07:57:32Z http://umpir.ump.edu.my/id/eprint/40759/ Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization Kamal Zuhairi, Zamli Din, Fakhrud Alhadawi, Hussam S. QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. Unlike most competing works (which typically integrate a single chaotic map into a particular metaheuristic algorithm), QL-NMR assembles five chaotic maps (i.e., Chebyshev, logistic, circle, Singer, and sinusoidal) as part of the algorithm itself. Using a Q-learning table, QL-NMR remembers the historical performance of each chaotic map during the S-box construction process allowing just-in-time adaptive selection based on its current performance. Experimental results for 8 × 8 S-box generation demonstrate that the proposed QL-NMR gives competitive performance against other existing works, particularly in terms of nonlinearity and strict avalanche criteria. To further demonstrate the effectiveness of our proposed work, we have subjected the QL-NMR for image segmentation using multilevel thresholding. The results confirm that QL-NMR gives better performance than its predecessor NMR. Finally, QL-NMR S-box also outperformed NMR S-box in image encryption. Springer Science and Business Media Deutschland GmbH 2023-05 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40759/1/Exploring%20a%20Q-learning-based%20chaotic%20naked%20mole%20rat%20algorithm.pdf pdf en http://umpir.ump.edu.my/id/eprint/40759/2/Exploring%20a%20Q-learning-based%20chaotic%20naked%20mole%20rat%20algorithm%20for%20S-box%20construction%20and%20optimization_ABS.pdf Kamal Zuhairi, Zamli and Din, Fakhrud and Alhadawi, Hussam S. (2023) Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization. Neural Computing and Applications, 35 (14). pp. 10449-10471. ISSN 0941-0643. (Published) https://doi.org/10.1007/s00521-023-08243-3 https://doi.org/10.1007/s00521-023-08243-3
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Kamal Zuhairi, Zamli
Din, Fakhrud
Alhadawi, Hussam S.
Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
description This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. Unlike most competing works (which typically integrate a single chaotic map into a particular metaheuristic algorithm), QL-NMR assembles five chaotic maps (i.e., Chebyshev, logistic, circle, Singer, and sinusoidal) as part of the algorithm itself. Using a Q-learning table, QL-NMR remembers the historical performance of each chaotic map during the S-box construction process allowing just-in-time adaptive selection based on its current performance. Experimental results for 8 × 8 S-box generation demonstrate that the proposed QL-NMR gives competitive performance against other existing works, particularly in terms of nonlinearity and strict avalanche criteria. To further demonstrate the effectiveness of our proposed work, we have subjected the QL-NMR for image segmentation using multilevel thresholding. The results confirm that QL-NMR gives better performance than its predecessor NMR. Finally, QL-NMR S-box also outperformed NMR S-box in image encryption.
format Article
author Kamal Zuhairi, Zamli
Din, Fakhrud
Alhadawi, Hussam S.
author_facet Kamal Zuhairi, Zamli
Din, Fakhrud
Alhadawi, Hussam S.
author_sort Kamal Zuhairi, Zamli
title Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
title_short Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
title_full Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
title_fullStr Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
title_full_unstemmed Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
title_sort exploring a q-learning-based chaotic naked mole rat algorithm for s-box construction and optimization
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/40759/1/Exploring%20a%20Q-learning-based%20chaotic%20naked%20mole%20rat%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/40759/2/Exploring%20a%20Q-learning-based%20chaotic%20naked%20mole%20rat%20algorithm%20for%20S-box%20construction%20and%20optimization_ABS.pdf
http://umpir.ump.edu.my/id/eprint/40759/
https://doi.org/10.1007/s00521-023-08243-3
https://doi.org/10.1007/s00521-023-08243-3
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score 13.232414

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