Model Access Control

Model Access Control is a governance mechanism that regulates and restricts authorized interactions with machine learning models by defining precise permissions, roles, and authentication protocols to ensure secure and auditable model usage within an organizational or system environment.

11

Publications

2.2K

Citations

48

Authors

28

Institutions

Publications per year

2017–2026

7

Authors

48

  1. CD
    Csaba Debreceni

    Budapest University of Technology and Economics, Hungary

    2 publications · 42 citations

    2

    h-index

  2. DV
    Dániel Varró

    Budapest University of Technology and Economics, Hungary

    2 publications · 42 citations

    2

    h-index

  3. GB
    Gábor Bergmann

    Budapest University of Technology and Economics, Hungary

    2 publications · 42 citations

    2

    h-index

  4. IR
    István Ráth

    Budapest University of Technology and Economics, Hungary

    2 publications · 42 citations

    2

    h-index

  5. LM
    Laurent Michel

    University of Connecticut, United States

    1 publications · 22 citations

    1

    h-index

1–5 of 48

Venues

  1. IEEE Access

    1 publications · 26 citations

    1

    h-index

  2. Environmental Modelling & Software

    1 publications · 147 citations

    1

    h-index

  3. 1

    h-index

  4. PharmacoEconomics

    1 publications · 14 citations

    1

    h-index

  5. Medical Entomology and Zoology

    1 publications · 1.7K citations

    1

    h-index

1–5