Privacy Amplification via Shuffling: Unified, Simplified, and Tightened
Summary: Variation-ratio reduction: unified, tighter privacy-amplification framework for the shuffle model using total-variation and blanket probability-ratio parameters, covering both single- and multi-message protocols. Offers exact tightness for extremal randomizers, improved parallel-composition accounting, and an O(n) numeric amplifier with major privacy-budget savings. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shaowei Wang (Guangdong University of Technology)
- 2. Yun Peng (Guangdong University of Technology)
- 3. Jin Li (Guangdong University of Technology)
- 4. Zikai Wen (Virginia Polytechnic Institute and State University)
- 5. Zhipeng Li (Guangdong University of Technology)
- 6. Shiyu Yu (Guangdong University of Technology)
- 7. Di Wang (King Abdullah University of Science and Technology)
- 8. Wei Yang (University of Science and Technology Beijing)
BibTeX Citation
@article{wang_vldb24,
title = {{Privacy Amplification via Shuffling: Unified, Simplified, and Tightened}},
author = {Wang, Shaowei and Peng, Yun and Li, Jin and Wen, Zikai and Li, Zhipeng and Yu, Shiyu and Wang, Di and Yang, Wei},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {8},
pages = {1870--1883},
doi = {10.14778/3659437.3659444},
url = {https://doi.org/10.14778/3659437.3659444},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,147 | Analysis of Shuffling Beyond Pure Local Differential Privacy | 2026 | PODS | 5.093636e-05 |
| 10,517 | Doppio: Communication-Efficient and Secure Multi-Party Shuffle Differential Privacy | 2026 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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