Fragments and Loose Associations: Respecting Privacy in Data Publishing
Summary: Data fragmentation to satisfy confidentiality constraints and visibility requests; split sensitive attribute associations while preserving usable views. Broken associations released as sanitized loose associations with a defined privacy level to enable protected publication. (summarized by gpt-5-nano on Feb 09 2026)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 654 | Anatomy: Simple and Effective Privacy Preservation | 2006 | VLDB | 0.00018613167 |
| 1,633 | Injecting Utility into Anonymized Datasets | 2006 | SIGMOD | 0.00011060784 |
| 2,119 | Two Can Keep a Secret: A Distributed Architecture for Secure Database Services | 2005 | CIDR | 9.5090272e-05 |
| 2,718 | Anonymizing Bipartite Graph Data using Safe Groupings | 2008 | VLDB | 8.2409647e-05 |
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