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A Systematic Review on Password Guessing Tasks
by
Ni, Lulin
, Yin, Hao
, He, Liangliang
, Ji, Qingbing
, Yu, Wei
, Yin, Qingsong
, Xiao, Wei
, Chang, Tao
in
Algorithms
/ Artificial intelligence
/ Cybersecurity
/ Cyberterrorism
/ Data security
/ Deep learning
/ Internet
/ Machine learning
/ Neural networks
/ password guessing
/ Passwords
/ Performance evaluation
/ R&D
/ Research & development
/ Review
/ Self report
/ Semantics
/ Software
/ targeted password guessing
/ Taxonomy
/ Trawling
/ trawling password guessing
/ User behavior
2023
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A Systematic Review on Password Guessing Tasks
by
Ni, Lulin
, Yin, Hao
, He, Liangliang
, Ji, Qingbing
, Yu, Wei
, Yin, Qingsong
, Xiao, Wei
, Chang, Tao
in
Algorithms
/ Artificial intelligence
/ Cybersecurity
/ Cyberterrorism
/ Data security
/ Deep learning
/ Internet
/ Machine learning
/ Neural networks
/ password guessing
/ Passwords
/ Performance evaluation
/ R&D
/ Research & development
/ Review
/ Self report
/ Semantics
/ Software
/ targeted password guessing
/ Taxonomy
/ Trawling
/ trawling password guessing
/ User behavior
2023
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Do you wish to request the book?
A Systematic Review on Password Guessing Tasks
by
Ni, Lulin
, Yin, Hao
, He, Liangliang
, Ji, Qingbing
, Yu, Wei
, Yin, Qingsong
, Xiao, Wei
, Chang, Tao
in
Algorithms
/ Artificial intelligence
/ Cybersecurity
/ Cyberterrorism
/ Data security
/ Deep learning
/ Internet
/ Machine learning
/ Neural networks
/ password guessing
/ Passwords
/ Performance evaluation
/ R&D
/ Research & development
/ Review
/ Self report
/ Semantics
/ Software
/ targeted password guessing
/ Taxonomy
/ Trawling
/ trawling password guessing
/ User behavior
2023
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Journal Article
A Systematic Review on Password Guessing Tasks
2023
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Overview
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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