Database Paper Browser

Back to papers

Privacy Preservation by Disassociation

Summary: Proposes disassociation, a data-anonymization method for sparse multidimensional data that preserves terms while hiding co-occurrence. Shows k^m-anonymity by suppressing co-location, not term hiding; benchmarked against generalization and differential privacy. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10533
Venue
VLDB
Year
2012
Pagerank
4.427232e-05
Overall Rank
8,930 | 37.88%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,046 Aegis: A Correlation-Based Data Masking Advisor for Data-Sharing Ecosystems 2026 SIGMOD 4.1945683e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers

Overall Rank Paper Year Venue Pagerank
3,304 Plausible Deniability for Privacy-Preserving Data Synthesis 2017 VLDB 7.2467347e-05
7,541 Privacy-Enhancing k-Anonymization of Customer Data 2005 PODS 4.7157092e-05
1,735 On k-Anonymity and the Curse of Dimensionality 2005 VLDB 0.00010723402
12,229 Non-homogeneous Generalization in Privacy Preserving Data Publishing 2010 SIGMOD 4.1945683e-05
455 Incognito: Efficient Full-Domain K-Anonymity 2005 SIGMOD 0.00022717354
2,682 Personalized Privacy Preservation 2006 SIGMOD 8.3202837e-05
225 Generalizing Data to Provide Anonymity when Disclosing Information 1998 PODS 0.00032707646
2,815 Achieving Anonymity via Clustering 2006 PODS 8.0702535e-05
4,979 Fast Data Anonymization with Low Information Loss 2007 VLDB 5.7878768e-05
3,381 Privacy-preserving Anonymization of Set-valued Data 2008 VLDB 7.1604078e-05