Fast Data Anonymization with Low Information Loss
Summary: One-dimensional quasi-identifiers enable linear-time heuristics for k-anonymity and l-diversity with meaningful information-loss metrics. Space-mapping generalizes to multi-dimensional data, yielding faster anonymization with lower loss and beating state-of-the-art in time and quality. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Gabriel Ghinita
- 2. Panagiotis Karras
- 3. Panos Kalnis
- 4. Nikos Mamoulis
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,404 | Attacks on Privacy and deFinetti's Theorem | 2009 | SIGMOD | 8.8736984e-05 |
| 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 |
| 9,341 | Small Domain Randomization: Same Privacy, More Utility | 2010 | VLDB | 4.351469e-05 |
| 9,343 | Preservation of Proximity Privacy in Publishing Numerical Sensitive Data | 2008 | SIGMOD | 4.351469e-05 |
| 10,046 | Aegis: A Correlation-Based Data Masking Advisor for Data-Sharing Ecosystems | 2026 | SIGMOD | 4.1905499e-05 |
| 11,473 | When the Recursive Diversity Anonymity Meets the Ring Signature | 2021 | SIGMOD | 4.1905499e-05 |
| 12,237 | Non-homogeneous Generalization in Privacy Preserving Data Publishing | 2010 | SIGMOD | 4.1905499e-05 |
| 12,335 | TIAMAT: a Tool for Interactive Analysis of Microdata Anonymization Techniques | 2009 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11 | Implementing Data Cubes Efficiently | 1996 | SIGMOD | 0.0011695087 |
| 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 |
| 654 | Anatomy: Simple and Effective Privacy Preservation | 2006 | VLDB | 0.00018594644 |
| 1,639 | Injecting Utility into Anonymized Datasets | 2006 | SIGMOD | 0.00011049413 |
| 2,656 | Personalized Privacy Preservation | 2006 | SIGMOD | 8.3636527e-05 |
| 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 |
| 4,527 | Anonymization of Set-Valued Data via Top-Down, Local Generalization | 2009 | VLDB | 6.1076171e-05 |
| 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 |
| 225 | Generalizing Data to Provide Anonymity when Disclosing Information | 1998 | PODS | 0.0003266103 |
| 6,476 | Approximate Algorithms for k-Anonymity | 2007 | SIGMOD | 5.040879e-05 |
| 2,822 | Achieving Anonymity via Clustering | 2006 | PODS | 8.0624025e-05 |
| 8,934 | Privacy Preservation by Disassociation | 2012 | VLDB | 4.4229886e-05 |
| 3,382 | Privacy-preserving Anonymization of Set-valued Data | 2008 | VLDB | 7.1538038e-05 |