On k-Anonymity and the Curse of Dimensionality
Summary: Analyzes k-anonymity in high-dimensional data by modeling inference attacks over all attribute combinations. Demonstrates dimensionality-driven sparsity and an exponential attack space, forcing either heavy data suppression or privacy compromise. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 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 |
| 1,566 | PrivBasis: Frequent Itemset Mining with Differential Privacy | 2012 | VLDB | 0.00011324162 |
| 1,639 | Injecting Utility into Anonymized Datasets | 2006 | SIGMOD | 0.00011049413 |
| 2,656 | Personalized Privacy Preservation | 2006 | SIGMOD | 8.3636527e-05 |
| 3,788 | Time Series Compressibility and Privacy | 2007 | VLDB | 6.7624343e-05 |
| 4,791 | Hiding the Presence of Individuals from Shared Databases | 2007 | SIGMOD | 5.9135123e-05 |
| 6,476 | Approximate Algorithms for k-Anonymity | 2007 | SIGMOD | 5.040879e-05 |
| 8,791 | Dynamic Anonymization: Accurate Statistical Analysis with Privacy Preservation | 2008 | SIGMOD | 4.4459403e-05 |
| 8,934 | Privacy Preservation by Disassociation | 2012 | VLDB | 4.4229886e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 40 | Privacy-Preserving Data Mining | 2000 | SIGMOD | 0.00074213516 |
| 148 | On the Design and Quantification of Privacy Preserving Data Mining Algorithms | 2001 | PODS | 0.00041196325 |
| 305 | On the Complexity of Optimal K-Anonymity | 2004 | PODS | 0.00028264843 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,229 | On the Risks of Collecting Multidimensional Data Under Local Differential Privacy | 2023 | VLDB | 4.1905499e-05 |
| 225 | Generalizing Data to Provide Anonymity when Disclosing Information | 1998 | PODS | 0.0003266103 |
| 2,436 | Optimizing error of high-dimensional statistical queries under differential privacy | 2018 | VLDB | 8.8217855e-05 |
| 12,320 | Anonymized Data: Generation, Models, Usage | 2009 | SIGMOD | 4.1905499e-05 |
| 458 | Incognito: Efficient Full-Domain K-Anonymity | 2005 | SIGMOD | 0.00022698513 |
| 7,475 | Privacy-Enhancing k-Anonymization of Customer Data | 2005 | PODS | 4.714352e-05 |
| 2,822 | Achieving Anonymity via Clustering | 2006 | PODS | 8.0624025e-05 |
| 3,382 | Privacy-preserving Anonymization of Set-valued Data | 2008 | VLDB | 7.1538038e-05 |
| 8,934 | Privacy Preservation by Disassociation | 2012 | VLDB | 4.4229886e-05 |
| 4,981 | Fast Data Anonymization with Low Information Loss | 2007 | VLDB | 5.7823243e-05 |