Improving Utility and Security of the Shuffler-based Differential Privacy
Summary: Analyzes shuffler-based LDP with an explicit treatment of adversaries in the multi-party model. Proposes a stronger privacy–utility algorithm and a shuffling protocol resilient to broader attacks, validated experimentally. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Tianhao Wang (Purdue University)
- 2. Bolin Ding (Alibaba)
- 3. Min Xu (University of Chicago)
- 4. Zhicong Huang (Alibaba)
- 5. Cheng Hong (Alibaba)
- 6. Jingren Zhou (Alibaba)
- 7. Ninghui Li (Purdue University)
- 8. Somesh Jha (University of Wisconsin)
BibTeX Citation
@article{wang_vldb20,
title = {{Improving Utility and Security of the Shuffler-based Differential Privacy}},
author = {Wang, Tianhao and Ding, Bolin and Xu, Min and Huang, Zhicong and Hong, Cheng and Zhou, Jingren and Li, Ninghui and Jha, Somesh},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {13},
pages = {3545--3558},
doi = {10.14778/3424573.3424576},
url = {https://doi.org/10.14778/3424573.3424576},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,657 | Network Shuffling: Privacy Amplification via Random Walks | 2022 | SIGMOD | 5.2937663e-05 |
| 10,631 | Defense against Poisoning Attacks under Shuffle-DP | 2026 | SIGMOD | 4.9793485e-05 |
| 10,702 | Doppio: Communication-Efficient and Secure Multi-Party Shuffle Differential Privacy | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,336 | Answering Multi-Dimensional Analytical Queries under Local Differential Privacy | 2019 | SIGMOD | 8.6206562e-05 |
| 2,867 | CryptEpsilon: Crypto-Assisted Differential Privacy on Untrusted Servers | 2020 | SIGMOD | 7.9248931e-05 |
| 4,214 | Answering Multi-Dimensional Range Queries under Local Differential Privacy | 2021 | VLDB | 6.7295366e-05 |
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| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,794 | Optimal Random Perturbation at Multiple Privacy Levels | 2009 | VLDB |
| 2 | 11,244 | Privacy for Free: Leveraging Local Differential Privacy Perturbed Data from Multiple Services | 2025 | VLDB |
| 3 | 3,234 | LDP-IDS: Local Differential Privacy for Infinite Data Streams | 2022 | SIGMOD |
| 4 | 10,364 | Analysis of Shuffling Beyond Pure Local Differential Privacy | 2026 | PODS |
| 5 | 7,604 | Privacy Amplification by Sampling under User-level Differential Privacy | 2024 | SIGMOD |
| 6 | 10,702 | Doppio: Communication-Efficient and Secure Multi-Party Shuffle Differential Privacy | 2026 | VLDB |
| 7 | 10,639 | Enhancing Local Differential Privacy Accuracy by Exploiting Inherent Uncertainty | 2026 | SIGMOD |
| 8 | 11,742 | On the Risks of Collecting Multidimensional Data Under Local Differential Privacy | 2023 | VLDB |
| 9 | 8,657 | Network Shuffling: Privacy Amplification via Random Walks | 2022 | SIGMOD |
| 10 | 5,726 | Privacy Amplification via Shuffling: Unified, Simplified, and Tightened | 2024 | VLDB |