Privacy Implications of Database Ranking
Summary: Shows that top-k ranks can leak attributes hidden from query results when ranking uses private fields. Introduces a query-interface/adversary taxonomy and inference attacks validated theoretically, experimentally, and against large real-world web databases. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Md Farhadur Rahman (University of Texas)
- 2. Weimo Liu (George Washington University)
- 3. Saravanan Thirumuruganathan (University of Texas)
- 4. Nan Zhang (George Washington University)
- 5. Gautam Das (University of Texas)
BibTeX Citation
@article{rahman_vldb15,
title = {{Privacy Implications of Database Ranking}},
author = {Rahman, Md Farhadur and Liu, Weimo and Thirumuruganathan, Saravanan and Zhang, Nan and Das, Gautam},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {10},
pages = {1106--1117},
doi = {10.14778/2794367.2794379},
url = {https://doi.org/10.14778/2794367.2794379},
year = {2015}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,925 | Heterogeneous Recommendations: What You Might Like To Read After Watching Interstellar | 2017 | VLDB | 5.5181056e-05 |
Previous
Page 1 / 1
Next
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 |
|---|---|---|---|---|
| 5 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0010828372 |
| 466 | Automated Ranking of Database Query Results | 2003 | CIDR | 0.00018014467 |
| 1,100 | Range Queries in OLAP Data Cubes | 1997 | SIGMOD | 0.00012169143 |
| 1,327 | A Unified Approach to Ranking in Probabilistic Databases | 2009 | VLDB | 0.00011141552 |
| 1,844 | Probabilistic Ranking of Database Query Results | 2004 | VLDB | 9.6314187e-05 |
| 5,868 | A Random Walk Approach to Sampling Hidden Databases | 2007 | SIGMOD | 6.0613238e-05 |
| 8,671 | Unbiased Estimation of Size and Other Aggregates Over Hidden Web Databases | 2010 | SIGMOD | 5.3876663e-05 |
| 12,285 | Rank Discovery From Web Databases | 2013 | VLDB | 5.093636e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 7,299 | Efficient and Generic Evaluation of Ranked Queries | 2011 | SIGMOD |
| 2 | 466 | Automated Ranking of Database Query Results | 2003 | CIDR |
| 3 | 1,844 | Probabilistic Ranking of Database Query Results | 2004 | VLDB |
| 4 | 2,300 | Principled Evaluation of Differentially Private Algorithms using DPBench | 2016 | SIGMOD |
| 5 | 8,378 | Discovering the Skyline of Web Databases | 2016 | VLDB |
| 6 | 12,495 | Privacy Preservation of Aggregates in Hidden Databases: Why and How? | 2009 | SIGMOD |
| 7 | 12,083 | Query Reranking As A Service | 2016 | VLDB |
| 8 | 4,625 | Practical Private Range Search Revisited | 2016 | SIGMOD |
| 9 | 1,310 | A Privacy-Preserving Index for Range Queries | 2004 | VLDB |
| 10 | 12,285 | Rank Discovery From Web Databases | 2013 | VLDB |