Privacy-preserving Anonymization of Set-valued Data
Summary: Set-valued data anonymization using a generalization-based k^m-anonymity variant to bound dimensionality; items treated as quasi-identifiers and sensitive data. Optimal algorithm (costly) and two scalable greedy heuristics, evaluated on real datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Manolis Terrovitis
- 2. Nikos Mamoulis
- 3. Panos Kalnis
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,567 | PrivBasis: Frequent Itemset Mining with Differential Privacy | 2012 | VLDB | 0.0001133268 |
| 2,685 | On Differentially Private Frequent Itemset Mining | 2013 | VLDB | 8.3070708e-05 |
| 3,097 | Publishing Set-Valued Data via Differential Privacy | 2011 | VLDB | 7.5647028e-05 |
| 4,524 | Anonymization of Set-Valued Data via Top-Down, Local Generalization | 2009 | VLDB | 6.1133444e-05 |
| 5,483 | rho-uncertainty: Inference-Proof Transaction Anonymization | 2010 | VLDB | 5.4828795e-05 |
| 8,074 | Set-valued Data Publication with Local Privacy: Tight Error Bounds and Efficient Mechanisms | 2020 | VLDB | 4.5918992e-05 |
| 8,930 | Privacy Preservation by Disassociation | 2012 | VLDB | 4.427232e-05 |
| 12,312 | Anonymized Data: Generation, Models, Usage | 2009 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 181 | Mining Frequent Patterns without Candidate Generation | 2000 | SIGMOD | 0.00036992674 |
| 304 | On the Complexity of Optimal K-Anonymity | 2004 | PODS | 0.00028290121 |
| 455 | Incognito: Efficient Full-Domain K-Anonymity | 2005 | SIGMOD | 0.00022717354 |
| 654 | Anatomy: Simple and Effective Privacy Preservation | 2006 | VLDB | 0.00018613167 |
| 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 |
| 6,482 | Approximate Algorithms for k-Anonymity | 2007 | SIGMOD | 5.045711e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,541 | Privacy-Enhancing k-Anonymization of Customer Data | 2005 | PODS | 4.7157092e-05 |
| 1,382 | Minimality Attack in Privacy Preserving Data Publishing | 2007 | VLDB | 0.00012281313 |
| 2,815 | Achieving Anonymity via Clustering | 2006 | PODS | 8.0702535e-05 |
| 12,229 | Non-homogeneous Generalization in Privacy Preserving Data Publishing | 2010 | SIGMOD | 4.1945683e-05 |
| 225 | Generalizing Data to Provide Anonymity when Disclosing Information | 1998 | PODS | 0.00032707646 |
| 4,524 | Anonymization of Set-Valued Data via Top-Down, Local Generalization | 2009 | VLDB | 6.1133444e-05 |
| 3,097 | Publishing Set-Valued Data via Differential Privacy | 2011 | VLDB | 7.5647028e-05 |
| 2,682 | Personalized Privacy Preservation | 2006 | SIGMOD | 8.3202837e-05 |
| 8,930 | Privacy Preservation by Disassociation | 2012 | VLDB | 4.427232e-05 |
| 4,979 | Fast Data Anonymization with Low Information Loss | 2007 | VLDB | 5.7878768e-05 |