Secure Data Federation
Secure Data Federation is a data integration framework that enables controlled, privacy-preserving access to distributed datasets across organizational or jurisdictional boundaries without centralizing the data, thereby maintaining local autonomy and security policies.
12
Publications
948
Citations
77
Authors
41
Institutions
Publications per year
2017–2026
4
Parents
12
A Secure Federated Transfer Learning Framework
Yang Liu, Yan Kang, Chaoping Xing et al. · IEEE Intelligent Systems · 2020 · 612 citations · Full text
Yongxin Tong, Xuchen Pan, Yuxiang Zeng et al. · Proceedings of the VLDB Endowment · 2022 · 56 citations
Adding Federated Identity Management to OpenStack
David Chadwick, Kristy Siu, Craig A. Lee et al. · Journal of Grid Computing · 2013 · 56 citations · Full text
1–5 of 12
77
2
h-index
2
h-index
Hong Kong University of Science and Technology, Hong Kong SAR China
2 publications · 68 citations
2
h-index
Hong Kong University of Science and Technology, Hong Kong SAR China
2 publications · 68 citations
2
h-index
2
h-index
1–5 of 77
41
Singapore Management University
Singapore, Singapore
2 h-index
2 publications
68 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
2 h-index
3 publications
636 citations
University of Memphis
Memphis, United States
2 h-index
2 publications
68 citations

Beihang University
Beijing, China
2 h-index
16 publications
588 citations
University of Bergen
Bergen, Norway
2 h-index
2 publications
69 citations

University of Oslo
Oslo, Norway
1 h-index
1 publications
15 citations

Finnish Institute for Health and Welfare
Helsinki, Finland
1 h-index
1 publications
54 citations
Microsoft (United States)
Redmond, United States
1 h-index
1 publications
19 citations
1–8 of 41
PVLDB · 2 publications · 68 citations
2
h-index
JSS · 1 publications · 19 citations
1
h-index
1 publications · 612 citations
1
h-index
1 publications · 54 citations
1
h-index
1 publications · 63 citations
1
h-index
1–5