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
Parents
11
MLCapsule: Guarded Offline Deployment of Machine Learning as a Service
Lucjan Hanzlik, Yang Zhang, Kathrin Grosse et al. · 2021 · 41 citations · Full text
Isabell Lederer, Rudolf Mayer, Andreas Rauber · IEEE Transactions on Neural Networks and Learning Systems · 2023 · 31 citations · Full text
1–5 of 11
48
Budapest University of Technology and Economics, Hungary
2 publications · 42 citations
2
h-index
2
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2
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2
h-index
1
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1–5 of 48
28

Budapest University of Technology and Economics
Budapest, Hungary
2 h-index
7 publications
154 citations
University of Florence
Florence, Italy
1 h-index
2 publications
294 citations
Jet Propulsion Laboratory
Pasadena, United States
1 h-index
1 publications
147 citations
Institute for Clinical and Economic Review
Boston, United States
1 h-index
2 publications
28 citations

University of Cagliari
Cagliari, Italy
1 h-index
1 publications
41 citations

Universidad Católica del Norte
Antofagasta, Chile
1 h-index
1 publications
22 citations

University of Colorado Denver
Denver, United States
1 h-index
3 publications
42 citations
California Institute of Technology
Pasadena, United States
1 h-index
1 publications
147 citations
1–8 of 28
1 publications · 26 citations
1
h-index
1 publications · 147 citations
1
h-index
1 publications · 31 citations
1
h-index
1 publications · 14 citations
1
h-index
1 publications · 1.7K citations
1
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1–5