Privacy-preserving Distributed Analytics
Privacy-Preserving Distributed Analytics is a distributed data analysis paradigm that enables multiple parties to collaboratively derive insights from decentralized data sources while enforcing privacy-preserving mechanisms to prevent the exposure of sensitive information during computation.
40
Publications
4K
Citations
154
Authors
85
Institutions
Publications per year
2017–2026
23
Parents
40
Tools for privacy preserving distributed data mining
Chris Clifton, Murat Kantarcıoğlu, Jaideep Vaidya et al. · ACM SIGKDD Explorations Newsletter · 2002 · 890 citations
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154
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École Polytechnique Fédérale de Lausanne, Switzerland
2 publications · 217 citations
2
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École Polytechnique Fédérale de Lausanne, Switzerland
2 publications · 217 citations
2
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2
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2
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1–5 of 154
85
Purdue University West Lafayette
West Lafayette, United States
3 h-index
8 publications
6.4K citations
University of Pennsylvania
Philadelphia, United States
3 h-index
14 publications
706 citations
Emory University
Atlanta, United States
3 h-index
4 publications
132 citations
IIT@MIT
Cambridge, United States
2 h-index
2 publications
217 citations
Google (United States)
Mountain View, United States
2 h-index
3 publications
94 citations
University Hospital Cologne
Cologne, Germany
2 h-index
2 publications
54 citations
The University of Texas at Dallas
Richardson, United States
2 h-index
3 publications
78 citations
University of Lausanne
Lausanne, Switzerland
2 h-index
6 publications
651 citations
1–8 of 85
TKDE · 2 publications · 174 citations
2
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2 publications · 64 citations
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Repository · 2 publications · 81 citations
2
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TDSC · 2 publications · 50 citations
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1 publications · 18 citations
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