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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)

Paper ID
10071
Venue
VLDB
Year
2010
Pagerank
4.1945683e-05
Overall Rank
12,273 | 14.62%
DOI
-

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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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