Sensitive Data Anonymization
Sensitive Data Anonymization is a methodological process within open data policy that systematically removes or obfuscates personally identifiable and confidential information from datasets to prevent re-identification, thereby enabling data sharing while preserving individual privacy.
450
Publications
45.1K
Citations
1.1K
Authors
467
Institutions
Publications per year
2017–2026
167
Parents
450
Ashwin Machanavajjhala, Daniel Kifer, Johannes Gehrke et al. · ACM Transactions on Knowledge Discovery from Data · 2007 · 3.6K citations
t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
Ninghui Li, Tiancheng Li, Suresh Venkatasubramanian · 2007 · 3.4K citations
L-diversity: privacy beyond k-anonymity
Ashwin Machanavajjhala, Johannes Gehrke, Daniel Kifer et al. · 2006 · 2.4K citations
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467

Universitat Rovira i Virgili
Tarragona, Spain
12 h-index
29 publications
2K citations
Simon Fraser University
Burnaby, Canada
11 h-index
19 publications
4.5K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
11 h-index
26 publications
4K citations

Concordia University
Montreal, Canada
10 h-index
22 publications
1.6K citations
Purdue University West Lafayette
West Lafayette, United States
9 h-index
17 publications
7.3K citations
University of Oxford
Oxford, United Kingdom
7 h-index
11 publications
383 citations
Emory University
Atlanta, United States
7 h-index
12 publications
364 citations

University of Southern Queensland
Toowoomba, Australia
7 h-index
13 publications
923 citations
1–8 of 467
Repository · 13 publications · 328 citations
12
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PVLDB · 10 publications · 728 citations
10
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TKDE · 10 publications · 884 citations
10
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Repository · 7 publications · 1.2K citations
7
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6 publications · 283 citations
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