Evolution of group-theoretic cryptology attacks using hyper-heuristics

In previous work, we developed a single evolutionary algorithm (EA) to solve random instances of the Anshel–Anshel–Goldfeld (AAG) key exchange protocol over polycyclic groups. The EA consisted of six simple heuristics which manipulated strings. The present work extends this by exploring the use of h...

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Autores principales:	Craven Matthew J., Woodward John R.
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	evolutionary algorithms polycyclic groups cryptography anshel–anshel–goldfeld key exchange protocol hyper–heuristic machine learning 20p05 68w30 90c27 94a60 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/92fdbd5fd096448b8aee398e7b8132e7
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id	oai:doaj.org-article:92fdbd5fd096448b8aee398e7b8132e7
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spelling	oai:doaj.org-article:92fdbd5fd096448b8aee398e7b8132e72021-12-05T14:10:52ZEvolution of group-theoretic cryptology attacks using hyper-heuristics1862-298410.1515/jmc-2021-0017https://doaj.org/article/92fdbd5fd096448b8aee398e7b8132e72021-10-01T00:00:00Zhttps://doi.org/10.1515/jmc-2021-0017https://doaj.org/toc/1862-2984In previous work, we developed a single evolutionary algorithm (EA) to solve random instances of the Anshel–Anshel–Goldfeld (AAG) key exchange protocol over polycyclic groups. The EA consisted of six simple heuristics which manipulated strings. The present work extends this by exploring the use of hyper-heuristics in group-theoretic cryptology for the first time. Hyper-heuristics are a way to generate new algorithms from existing algorithm components (in this case, simple heuristics), with EAs being one example of the type of algorithm which can be generated by our hyper-heuristic framework. We take as a starting point the above EA and allow hyper-heuristics to build on it by making small tweaks to it. This adaptation is through a process of taking the EA and injecting chains of heuristics built from the simple heuristics. We demonstrate we can create novel heuristic chains, which when placed in the EA create algorithms that out perform the existing EA. The new algorithms solve a greater number of random AAG instances than the EA. This suggests the approach may be applied to many of the same kinds of problems, providing a framework for the solution of cryptology problems over groups. The contribution of this article is thus a framework to automatically build algorithms to attack cryptology problems given an applicable group.Craven Matthew J.Woodward John R.De Gruyterarticleevolutionary algorithmspolycyclic groupscryptographyanshel–anshel–goldfeld key exchange protocolhyper–heuristicmachine learning20p0568w3090c2794a60MathematicsQA1-939ENJournal of Mathematical Cryptology, Vol 16, Iss 1, Pp 49-63 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	evolutionary algorithms polycyclic groups cryptography anshel–anshel–goldfeld key exchange protocol hyper–heuristic machine learning 20p05 68w30 90c27 94a60 Mathematics QA1-939
spellingShingle	evolutionary algorithms polycyclic groups cryptography anshel–anshel–goldfeld key exchange protocol hyper–heuristic machine learning 20p05 68w30 90c27 94a60 Mathematics QA1-939 Craven Matthew J. Woodward John R. Evolution of group-theoretic cryptology attacks using hyper-heuristics
description	In previous work, we developed a single evolutionary algorithm (EA) to solve random instances of the Anshel–Anshel–Goldfeld (AAG) key exchange protocol over polycyclic groups. The EA consisted of six simple heuristics which manipulated strings. The present work extends this by exploring the use of hyper-heuristics in group-theoretic cryptology for the first time. Hyper-heuristics are a way to generate new algorithms from existing algorithm components (in this case, simple heuristics), with EAs being one example of the type of algorithm which can be generated by our hyper-heuristic framework. We take as a starting point the above EA and allow hyper-heuristics to build on it by making small tweaks to it. This adaptation is through a process of taking the EA and injecting chains of heuristics built from the simple heuristics. We demonstrate we can create novel heuristic chains, which when placed in the EA create algorithms that out perform the existing EA. The new algorithms solve a greater number of random AAG instances than the EA. This suggests the approach may be applied to many of the same kinds of problems, providing a framework for the solution of cryptology problems over groups. The contribution of this article is thus a framework to automatically build algorithms to attack cryptology problems given an applicable group.
format	article
author	Craven Matthew J. Woodward John R.
author_facet	Craven Matthew J. Woodward John R.
author_sort	Craven Matthew J.
title	Evolution of group-theoretic cryptology attacks using hyper-heuristics
title_short	Evolution of group-theoretic cryptology attacks using hyper-heuristics
title_full	Evolution of group-theoretic cryptology attacks using hyper-heuristics
title_fullStr	Evolution of group-theoretic cryptology attacks using hyper-heuristics
title_full_unstemmed	Evolution of group-theoretic cryptology attacks using hyper-heuristics
title_sort	evolution of group-theoretic cryptology attacks using hyper-heuristics
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/92fdbd5fd096448b8aee398e7b8132e7
work_keys_str_mv	AT cravenmatthewj evolutionofgrouptheoreticcryptologyattacksusinghyperheuristics AT woodwardjohnr evolutionofgrouptheoreticcryptologyattacksusinghyperheuristics
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Evolution of group-theoretic cryptology attacks using hyper-heuristics

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