Password Entropy

Password Entropy is a metric in information security that quantifies the unpredictability of a password by measuring the logarithmic number of possible combinations an attacker must exhaustively search through to guess it, distinguishing it from other password strength indicators by its foundation in information theory.

22

Publications

2.3K

Citations

61

Authors

30

Institutions

Publications per year

2017–2026

5

Authors

61

  1. IO
    Ian Oakley

    Ulsan National Institute of Science and Technology, South Korea

    2 publications · 36 citations

    2

    h-index

  2. SK
    Saranga Komanduri

    Carnegie Mellon University, United States

    2 publications · 404 citations

    2

    h-index

  3. SS
    Shamik Sengupta

    University of Nevada, Reno, United States

    1 publications · 17 citations

    1

    h-index

  4. RK
    Ravi Kuber

    University of Maryland, Baltimore County, United States

    1 publications · 70 citations

    1

    h-index

  5. NC
    Nicolas Christin

    Carnegie Mellon University, United States

    1 publications · 349 citations

    1

    h-index

1–5 of 61

Venues

  1. 1

    h-index

  2. IEEE Transactions on Dependable and Secure Computing

    TDSC · 1 publications · 17 citations

    1

    h-index

  3. Americas Conference on Information Systems

    Conference · 1 publications · 10 citations

    1

    h-index

  4. 1

    h-index

  5. Procedia Computer Science

    1 publications · 11 citations

    1

    h-index

1–5