Differential Privacy and the US Census
Summary: Describes the US Census Bureau's adoption of differential privacy for the 2020 decennial, stressing DP's rigorous, composition-aware protection against arbitrary auxiliary information and adversaries. Reports theory-to-practice lessons from nationwide deployment and pinpoints open challenges in accuracy-privacy tradeoffs, algorithm design, and policy. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Cynthia Dwork (Harvard University)
BibTeX Citation
@inproceedings{dwork_pods19,
address = {New York, NY, USA},
series = {{PODS} '19},
title = {{Differential Privacy and the US Census}},
url = {https://dl.acm.org/doi/10.1145/3294052.3322188},
doi = {10.1145/3294052.3322188},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Dwork, Cynthia},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,205 | Sample Debiasing in the Themis Open World Database System | 2020 | SIGMOD | 6.8337021e-05 |
| 8,515 | Measuring Re-identification Risk | 2023 | SIGMOD | 5.4119882e-05 |
| 8,719 | DPXPlain: Privately Explaining Aggregate Query Answers | 2023 | VLDB | 5.3774243e-05 |
| 10,313 | Differentially Private Explanations for Clusters | 2026 | SIGMOD | 5.093636e-05 |
| 11,349 | DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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