Network Shuffling: Privacy Amplification via Random Walks
Summary: Decentralized shuffling via random-walk on a graph for privacy amplification in LDP. Distributed protocols, threat model, and amplification comparable to uniform shuffling; no centralized shuffler. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Seng Pei Liew (LINE Corporation)
- 2. Tsubasa Takahashi (LINE Corporation)
- 3. Shun Takagi (Kyoto University)
- 4. Fumiyuki Kato (Kyoto University)
- 5. Yang Cao (Kyoto University)
- 6. Masatoshi Yoshikawa (Kyoto University)
BibTeX Citation
@inproceedings{liew_sigmod22,
title = {{Network Shuffling: Privacy Amplification via Random Walks}},
author = {Liew, Seng Pei and Takahashi, Tsubasa and Takagi, Shun and Kato, Fumiyuki and Cao, Yang and Yoshikawa, Masatoshi},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3526162},
url = {https://dl.acm.org/doi/10.1145/3514221.3526162},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,345 | DP-starJ: A Differential Private Scheme towards Analytical Star-Join Queries | 2023 | SIGMOD | 5.1901916e-05 |
| 10,364 | Analysis of Shuffling Beyond Pure Local Differential Privacy | 2026 | PODS | 4.9793485e-05 |
| 10,702 | Doppio: Communication-Efficient and Secure Multi-Party Shuffle Differential Privacy | 2026 | VLDB | 4.9793485e-05 |
| 11,517 | Efficient Approximation of Kemeny’s Constant for Large Graphs | 2024 | SIGMOD | 4.9793485e-05 |
| 11,584 | Uldp-FL: Federated Learning with Across-Silo User-Level Differential Privacy | 2024 | 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 |
|---|---|---|---|---|
| 226 | Limiting Privacy Breaches in Privacy Preserving Data Mining | 2003 | PODS | 0.00023984903 |
| 2,867 | CryptEpsilon: Crypto-Assisted Differential Privacy on Untrusted Servers | 2020 | SIGMOD | 7.9248931e-05 |
| 5,575 | Improving Utility and Security of the Shuffler-based Differential Privacy | 2020 | VLDB | 6.0792754e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 226 | Limiting Privacy Breaches in Privacy Preserving Data Mining | 2003 | PODS |
| 2 | 7,604 | Privacy Amplification by Sampling under User-level Differential Privacy | 2024 | SIGMOD |
| 3 | 3,036 | Injecting Uncertainty in Graphs for Identity Obfuscation | 2012 | VLDB |
| 4 | 4,794 | Optimal Random Perturbation at Multiple Privacy Levels | 2009 | VLDB |
| 5 | 10,631 | Defense against Poisoning Attacks under Shuffle-DP | 2026 | SIGMOD |
| 6 | 7,092 | RM2: Answer Counting Queries Efficiently under Shuffle Differential Privacy | 2025 | SIGMOD |
| 7 | 10,702 | Doppio: Communication-Efficient and Secure Multi-Party Shuffle Differential Privacy | 2026 | VLDB |
| 8 | 10,364 | Analysis of Shuffling Beyond Pure Local Differential Privacy | 2026 | PODS |
| 9 | 5,575 | Improving Utility and Security of the Shuffler-based Differential Privacy | 2020 | VLDB |
| 10 | 5,726 | Privacy Amplification via Shuffling: Unified, Simplified, and Tightened | 2024 | VLDB |