Guessing Models
Guessing Models is a computational framework in password security research that characterizes the probabilistic strategies attackers use to infer user-chosen passwords by modeling the relative likelihood of password guessability based on empirical or heuristic distributions.
155
Publications
12.7K
Citations
354
Authors
158
Institutions
Publications per year
2017–2026
37
Parents
155
Unraveling in Guessing Games: An Experimental Study
Rosemarie Nagel · American Economic Review · 2007 · 1.5K citations
Password memorability and security: empirical results
Junjie Yan, A Blackwell, Ross Anderson et al. · IEEE Security & Privacy · 2004 · 692 citations
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354
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158
Carnegie Mellon University
Pittsburgh, United States
8 h-index
45 publications
9K citations

Indian Institute of Science Bangalore
Bengaluru, India
4 h-index
7 publications
185 citations
Microsoft (United States)
Redmond, United States
4 h-index
8 publications
664 citations

Carleton University
Ottawa, Canada
4 h-index
6 publications
267 citations
Fudan University
Shanghai, China
3 h-index
13 publications
524 citations
Virginia Tech
Blacksburg, United States
3 h-index
9 publications
335 citations
Ontario Tech University
Oshawa, Canada
3 h-index
6 publications
682 citations
National University of Ireland, Maynooth
Maynooth, Ireland
3 h-index
6 publications
128 citations
1–8 of 158
4 publications · 279 citations
4
h-index
4 publications · 100 citations
4
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4 publications · 81 citations
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4 publications · 177 citations
4
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Conference · 3 publications · 373 citations
3
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1–5