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A Systematic Review on Password Guessing Tasks

Recently, many password guessing algorithms have been proposed, seriously threatening cyber security. In this paper, we systematically review over thirty methods for password guessing published between 2016 and 2023. First, we introduce a taxonomy for classifying the existing methods into trawling g...

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Detalles Bibliográficos
Autores principales: Yu, Wei, Yin, Qingsong, Yin, Hao, Xiao, Wei, Chang, Tao, He, Liangliang, Ni, Lulin, Ji, Qingbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10528539/
https://www.ncbi.nlm.nih.gov/pubmed/37761602
http://dx.doi.org/10.3390/e25091303
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author Yu, Wei
Yin, Qingsong
Yin, Hao
Xiao, Wei
Chang, Tao
He, Liangliang
Ni, Lulin
Ji, Qingbing
author_facet Yu, Wei
Yin, Qingsong
Yin, Hao
Xiao, Wei
Chang, Tao
He, Liangliang
Ni, Lulin
Ji, Qingbing
author_sort Yu, Wei
collection PubMed
description Recently, many password guessing algorithms have been proposed, seriously threatening cyber security. In this paper, we systematically review over thirty methods for password guessing published between 2016 and 2023. First, we introduce a taxonomy for classifying the existing methods into trawling guessing and targeted guessing. Second, we present an extensive benchmark dataset that can assist researchers and practitioners in successive works. Third, we conduct a bibliometric analysis to present trends in this field and cross-citation between reviewed papers. Further, we discuss the open challenges of password guessing in terms of diverse application scenarios, guessing efficiency, and the combination of traditional and deep learning methods. Finally, this review presents future research directions to guide successive research and development of password guessing.
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spelling pubmed-105285392023-09-28 A Systematic Review on Password Guessing Tasks Yu, Wei Yin, Qingsong Yin, Hao Xiao, Wei Chang, Tao He, Liangliang Ni, Lulin Ji, Qingbing Entropy (Basel) Review Recently, many password guessing algorithms have been proposed, seriously threatening cyber security. In this paper, we systematically review over thirty methods for password guessing published between 2016 and 2023. First, we introduce a taxonomy for classifying the existing methods into trawling guessing and targeted guessing. Second, we present an extensive benchmark dataset that can assist researchers and practitioners in successive works. Third, we conduct a bibliometric analysis to present trends in this field and cross-citation between reviewed papers. Further, we discuss the open challenges of password guessing in terms of diverse application scenarios, guessing efficiency, and the combination of traditional and deep learning methods. Finally, this review presents future research directions to guide successive research and development of password guessing. MDPI 2023-09-07 /pmc/articles/PMC10528539/ /pubmed/37761602 http://dx.doi.org/10.3390/e25091303 Text en © 2023 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 Review
Yu, Wei
Yin, Qingsong
Yin, Hao
Xiao, Wei
Chang, Tao
He, Liangliang
Ni, Lulin
Ji, Qingbing
A Systematic Review on Password Guessing Tasks
title A Systematic Review on Password Guessing Tasks
title_full A Systematic Review on Password Guessing Tasks
title_fullStr A Systematic Review on Password Guessing Tasks
title_full_unstemmed A Systematic Review on Password Guessing Tasks
title_short A Systematic Review on Password Guessing Tasks
title_sort systematic review on password guessing tasks
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10528539/
https://www.ncbi.nlm.nih.gov/pubmed/37761602
http://dx.doi.org/10.3390/e25091303
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