Vulnerability Inference

Vulnerability Inference is a scholarly method within vulnerability intelligence that involves deriving previously unknown or implicit vulnerabilities in systems, software, or networks through analytical reasoning, data-driven models, or logical deduction from known artifacts, distinguishing it from direct vulnerability discovery by emphasizing indirect, evidence-based identification.

17

Publications

1.6K

Citations

57

Authors

27

Institutions

Publications per year

2017–2026

9

Authors

57

  1. MG
    Minzhe Guo

    Cincinnati Children's Hospital Medical Center, United States

    2 publications · 120 citations

    2

    h-index

  2. JA
    Ju An Wang

    Southern Polytechnic State University, United States

    2 publications · 120 citations

    2

    h-index

  3. ME
    Mathias Ekstedt

    KTH Royal Institute of Technology, Sweden

    2 publications · 122 citations

    2

    h-index

  4. NI
    Neville I. Robinson

    Flinders University, Australia

    1 publications · 208 citations

    1

    h-index

  5. ZZ
    Zuochang Zhang

    Guangxi University of Finance and Economics, China

    1 publications · 18 citations

    1

    h-index

1–5 of 57

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 1 publications · 51 citations

    1

    h-index

  2. Global Environmental Change

    1 publications · 599 citations

    1

    h-index

  3. Computers & Electrical Engineering

    1 publications · 86 citations

    1

    h-index

  4. Ground Water

    GW · 1 publications · 208 citations

    1

    h-index

  5. 1

    h-index

1–5