Deriving Private Information from Randomized Data
Summary: Correlations drive leakage in randomized data release; PCA and Bayes reconstructions quantify disclosure risk. Proposes correlated-noise randomization; increasing data-noise similarity reduces reconstruction accuracy; experiments validate privacy gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhengli Huang (Syracuse University)
- 2. Wenliang Du (Syracuse University)
- 3. Biao Chen (Syracuse University)
BibTeX Citation
@inproceedings{huang_sigmod05,
title = {{Deriving Private Information from Randomized Data}},
author = {Huang, Zhengli and Du, Wenliang and Chen, Biao},
series = {{SIGMOD} '05},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1066157.1066163},
url = {https://dl.acm.org/doi/10.1145/1066157.1066163},
year = {2005}
}
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,255 | Attacks on Privacy and deFinetti's Theorem | 2009 | SIGMOD | 8.8595313e-05 |
| 4,629 | Time Series Compressibility and Privacy | 2007 | VLDB | 6.5960717e-05 |
| 4,732 | Optimal Random Perturbation at Multiple Privacy Levels | 2009 | VLDB | 6.5343833e-05 |
| 4,837 | PrivateClean: Data Cleaning and Differential Privacy | 2016 | SIGMOD | 6.4845444e-05 |
| 9,001 | Dynamic Anonymization: Accurate Statistical Analysis with Privacy Preservation | 2008 | SIGMOD | 5.334788e-05 |
| 12,424 | Non-homogeneous Generalization in Privacy Preserving Data Publishing | 2010 | SIGMOD | 5.093636e-05 |
| 12,545 | Publishing Naive Bayesian Classifiers: Privacy without Accuracy Loss | 2009 | VLDB | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 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 |
| 218 | Limiting Privacy Breaches in Privacy Preserving Data Mining | 2003 | PODS | 0.00024420564 |
| 244 | On the Design and Quantification of Privacy Preserving Data Mining Algorithms | 2001 | PODS | 0.00023476901 |
| 1,217 | Maintaining Data Privacy in Association Rule Mining | 2002 | VLDB | 0.00011627624 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 123 | Revealing Information while Preserving Privacy | 2003 | PODS |
| 2 | 2,862 | Privacy via Pseudorandom Sketches | 2006 | PODS |
| 3 | 1,217 | Maintaining Data Privacy in Association Rule Mining | 2002 | VLDB |
| 4 | 3,375 | Bayesian Differential Privacy on Correlated Data | 2015 | SIGMOD |
| 5 | 4,732 | Optimal Random Perturbation at Multiple Privacy Levels | 2009 | VLDB |
| 6 | 12,809 | Privacy in Data Systems | 2003 | PODS |
| 7 | 9,485 | Small Domain Randomization: Same Privacy, More Utility | 2010 | VLDB |
| 8 | 70 | Privacy-Preserving Data Mining | 2000 | SIGMOD |
| 9 | 244 | On the Design and Quantification of Privacy Preserving Data Mining Algorithms | 2001 | PODS |
| 10 | 218 | Limiting Privacy Breaches in Privacy Preserving Data Mining | 2003 | PODS |