Non-homogeneous Generalization in Privacy Preserving Data Publishing
Summary: Proposes non-homogeneous generalization for k-anonymity, reducing utility loss by varying quasi-identifiers inside partitions. Offers verification, a randomized defense against algorithm-aware attacks, and a partitioning technique that boosts data utility. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. W. K. Wong (University of Hong Kong)
- 2. Nikos Mamoulis (University of Hong Kong)
- 3. David W. Cheung (University of Hong Kong)
BibTeX Citation
@inproceedings{wong_sigmod10,
title = {{Non-homogeneous Generalization in Privacy Preserving Data Publishing}},
author = {Wong, W. K. and Mamoulis, Nikos and Cheung, David W.},
series = {{SIGMOD} '10},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1807167.1807248},
url = {https://dl.acm.org/doi/10.1145/1807167.1807248},
year = {2010}
}
Incoming Citations (Sorted by Pagerank)
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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.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 70 | Privacy-Preserving Data Mining | 2000 | SIGMOD | 0.0003804755 |
| 384 | On the Complexity of Optimal K-Anonymity | 2004 | PODS | 0.00019510305 |
| 450 | Incognito: Efficient Full-Domain K-Anonymity | 2005 | SIGMOD | 0.00018155142 |
| 572 | Anatomy: Simple and Effective Privacy Preservation | 2006 | VLDB | 0.00016316092 |
| 1,010 | m-Invariance: Towards Privacy Preserving Re-publication of Dynamic Datasets | 2007 | SIGMOD | 0.00012684067 |
| 1,295 | Minimality Attack in Privacy Preserving Data Publishing | 2007 | VLDB | 0.00011272398 |
| 1,734 | The New Casper: Query Processing for Location Services without Compromising Privacy | 2006 | VLDB | 9.9009944e-05 |
| 2,255 | Attacks on Privacy and deFinetti's Theorem | 2009 | SIGMOD | 8.8595313e-05 |
| 4,559 | Deriving Private Information from Randomized Data | 2005 | SIGMOD | 6.6318893e-05 |
| 4,699 | Fast Data Anonymization with Low Information Loss | 2007 | VLDB | 6.5560796e-05 |
| 7,632 | K-Anonymization as Spatial Indexing: Toward Scalable and Incremental Anonymization | 2007 | VLDB | 5.5777517e-05 |
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