Approximate Algorithms for k-Anonymity
Summary: Proposes approximation algorithms for k-anonymity in data publishing, addressing linking attacks on quasi-identifiers. Delivers O(log k)-approximation guarantees and O(beta log k)-time variants, outperforming O(k) and O(k log k) baselines; experiments show practical gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Hyoungmin Park
- 2. Kyuseok Shim
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,382 | Privacy-preserving Anonymization of Set-valued Data | 2008 | VLDB | 7.1538038e-05 |
| 8,791 | Dynamic Anonymization: Accurate Statistical Analysis with Privacy Preservation | 2008 | SIGMOD | 4.4459403e-05 |
| 9,343 | Preservation of Proximity Privacy in Publishing Numerical Sensitive Data | 2008 | SIGMOD | 4.351469e-05 |
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Outgoing Citations (Sorted by Pagerank)
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 |
|---|---|---|---|---|
| 182 | Mining Frequent Patterns without Candidate Generation | 2000 | SIGMOD | 0.00036955562 |
| 225 | Generalizing Data to Provide Anonymity when Disclosing Information | 1998 | PODS | 0.0003266103 |
| 305 | On the Complexity of Optimal K-Anonymity | 2004 | PODS | 0.00028264843 |
| 458 | Incognito: Efficient Full-Domain K-Anonymity | 2005 | SIGMOD | 0.00022698513 |
| 1,733 | On k-Anonymity and the Curse of Dimensionality | 2005 | VLDB | 0.00010715774 |
| 2,822 | Achieving Anonymity via Clustering | 2006 | PODS | 8.0624025e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 12,237 | Non-homogeneous Generalization in Privacy Preserving Data Publishing | 2010 | SIGMOD | 4.1905499e-05 |
| 10,928 | Improved Approximation Algorithms for Relational Clustering | 2024 | PODS | 4.1905499e-05 |
| 7,475 | Privacy-Enhancing k-Anonymization of Customer Data | 2005 | PODS | 4.714352e-05 |
| 8,934 | Privacy Preservation by Disassociation | 2012 | VLDB | 4.4229886e-05 |
| 458 | Incognito: Efficient Full-Domain K-Anonymity | 2005 | SIGMOD | 0.00022698513 |
| 3,382 | Privacy-preserving Anonymization of Set-valued Data | 2008 | VLDB | 7.1538038e-05 |
| 225 | Generalizing Data to Provide Anonymity when Disclosing Information | 1998 | PODS | 0.0003266103 |
| 4,981 | Fast Data Anonymization with Low Information Loss | 2007 | VLDB | 5.7823243e-05 |
| 2,822 | Achieving Anonymity via Clustering | 2006 | PODS | 8.0624025e-05 |
| 305 | On the Complexity of Optimal K-Anonymity | 2004 | PODS | 0.00028264843 |