Catch a Blowfish Alive: A Demonstration of Policy-Aware Differential Privacy for Interactive Data Exploration
Summary: Demonstrates BlowfishDB, the first policy-aware DP system for interactive data exploration. Dynamic Blowfish privacy enables on-the-fly generation of smaller policies and representations at query time, preserving the same accuracy and privacy while reducing costs. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jiaxiang Liu (University of Waterloo)
- 2. Karl Knopf (University of Waterloo)
- 3. Yiqing Tan (University of Waterloo)
- 4. Bolin Ding (Alibaba)
- 5. Xi He (University of Waterloo)
BibTeX Citation
@article{liu_vldb21,
title = {{Catch a Blowfish Alive: A Demonstration of Policy-Aware Differential Privacy for Interactive Data Exploration}},
author = {Liu, Jiaxiang and Knopf, Karl and Tan, Yiqing and Ding, Bolin and He, Xi},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {12},
pages = {2859--2862},
doi = {10.14778/3476311.3476363},
url = {https://doi.org/10.14778/3476311.3476363},
year = {2021}
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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 |
|---|---|---|---|---|
| 64 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00038522486 |
| 276 | Towards Practical Differential Privacy for SQL Queries | 2018 | VLDB | 0.0002234348 |
| 1,166 | PrivateSQL: A Differentially Private SQL Query Engine | 2019 | VLDB | 0.00011731286 |
| 1,955 | GUPT: Privacy Preserving Data Analysis Made Easy | 2012 | SIGMOD | 9.3176117e-05 |
| 2,370 | Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies | 2014 | SIGMOD | 8.5616358e-05 |
| 3,883 | Personalized Social Recommendations - Accurate or Private? | 2011 | VLDB | 6.9485406e-05 |
| 5,184 | APEx: Accuracy-Aware Differentially Private Data Exploration | 2019 | SIGMOD | 6.2392459e-05 |
| 12,372 | Design of Policy-Aware Differentially Private Algorithms | 2016 | VLDB | 4.9793485e-05 |
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