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Privacy Preserving Serial Data Publishing By Role Composition

Summary: Privacy-preserving serial data publishing in dynamic databases; existing work assumes all sensitive values change, which is often false. HD-composition models mixed-change attributes (temporary vs permanent) and delivers theory + real-data experiments validating its effectiveness. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9720
Venue
VLDB
Year
2008
Pagerank
4.5392079e-05
Overall Rank
8,306 | 42.28%
DOI
-

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Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
458 Incognito: Efficient Full-Domain K-Anonymity 2005 SIGMOD 0.00022698513
633 m-Invariance: Towards Privacy Preserving Re-publication of Dynamic Datasets 2007 SIGMOD 0.00018881387
654 Anatomy: Simple and Effective Privacy Preservation 2006 VLDB 0.00018594644
1,382 Minimality Attack in Privacy Preserving Data Publishing 2007 VLDB 0.00012270633
2,656 Personalized Privacy Preservation 2006 SIGMOD 8.3636527e-05
4,791 Hiding the Presence of Individuals from Shared Databases 2007 SIGMOD 5.9135123e-05
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