Sensitive Data Minimization
Sensitive Data Minimization is a methodological principle within the domain of investigative confidentiality that mandates the systematic limitation of collecting, processing, and retaining only the minimum amount of personally identifiable or confidential information necessary to achieve the specific objectives of an investigation.
55
Publications
2.8K
Citations
188
Authors
92
Institutions
Publications per year
2017–2026
26
55
Differential privacy in control and network systems
Jorge Cortés, Geir E. Dullerud, Shuo Han et al. · 2016 · 223 citations
1–5 of 55
188
3
h-index
Istituto di Analisi dei Sistemi ed Informatica Antonio Ruberti, Italy
2 publications · 47 citations
2
h-index
2
h-index
Transportes Inovação e Sistemas (Portugal), Portugal
2 publications · 56 citations
2
h-index
2
h-index
1–5 of 188
92
Virginia Tech
Blacksburg, United States
3 h-index
11 publications
198 citations
Cisco Systems (United States)
San Jose, United States
2 h-index
2 publications
46 citations

Instituto Superior de Gestão
Lisbon, Portugal
2 h-index
2 publications
56 citations

University of Central Florida
Orlando, United States
2 h-index
2 publications
46 citations

Technische Universität Darmstadt
Darmstadt, Germany
2 h-index
2 publications
46 citations

Zhejiang University
Hangzhou, China
2 h-index
7 publications
211 citations

University of Waterloo
Waterloo, Canada
2 h-index
5 publications
475 citations
Erasmus University Rotterdam
Rotterdam, The Netherlands
2 h-index
2 publications
56 citations
1–8 of 92
2 publications · 56 citations
2
h-index
2 publications · 45 citations
2
h-index
2 publications · 65 citations
2
h-index
Repository · 1 publications · 25 citations
1
h-index
1 publications · 134 citations
1
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1–5