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1808.01394
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Distributed Differential Privacy via Shuffling
4 August 2018
Albert Cheu
Adam D. Smith
Jonathan R. Ullman
David Zeber
M. Zhilyaev
FedML
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Papers citing
"Distributed Differential Privacy via Shuffling"
50 / 207 papers shown
A General Framework for Per-record Differential Privacy
Xinghe Chen
Dajun Sun
Quanqing Xu
Wei Dong
148
0
0
24 Nov 2025
Mutual Information Bounds in the Shuffle Model
Pengcheng Su
Haibo Cheng
Ping Wang
FedML
410
0
0
19 Nov 2025
Bayesian Advantage of Re-Identification Attack in the Shuffle Model
Pengcheng Su
Haibo Cheng
Ping Wang
FedML
332
1
0
05 Nov 2025
Private Map-Secure Reduce: Infrastructure for Efficient AI Data Markets
Sameer Wagh
Kenneth Stibler
Shubham Gupta
Lacey Strahm
Irina Bejan
...
Dave Buckley
Ruchi Bhatia
Jack Bandy
Aayush Agarwal
Andrew Trask
114
0
0
03 Nov 2025
Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via
f
f
f
-Differential Privacy
Xiang Li
Buxin Su
Chendi Wang
Qi Long
Weijie J. Su
FedML
251
4
0
22 Oct 2025
Differentially Private Wasserstein Barycenters
Anming Gu
Sasidhar Kunapuli
Mark Bun
Edward Chien
Kristjan Greenewald
OT
335
1
0
03 Oct 2025
Federated Learning of Quantile Inference under Local Differential Privacy
Leheng Cai
Qirui Hu
Shuyuan Wu
FedML
167
0
0
26 Sep 2025
Piquant
ε
\varepsilon
ε
: Private Quantile Estimation in the Two-Server Model
Hannah Keller
Jacob Imola
Fabrizio Boninsegna
Rasmus Pagh
A. Chowdhury
142
0
0
17 Sep 2025
Practitioners' Perspectives on a Differential Privacy Deployment Registry
Priyanka Nanayakkara
Elena Ghazi
Salil Vadhan
239
1
0
16 Sep 2025
Network-Aware Differential Privacy
Zhou Li
Yu Zheng
Tianhao Wang
Sang-Woo Jun
191
0
0
04 Sep 2025
Augmented Shuffle Differential Privacy Protocols for Large-Domain Categorical and Key-Value Data
Takao Murakami
Yuichi Sei
Reo Eriguchi
183
0
0
02 Sep 2025
Practical and Private Hybrid ML Inference with Fully Homomorphic Encryption
Sayan Biswas
Philippe Chartier
Akash Dhasade
Tom Jurien
David Kerriou
Anne-Marie Kerrmarec
Mohammed Lemou
Franklin Tranie
M. Vos
Milos Vujasinovic
195
1
0
01 Sep 2025
Differentially Private aggregate hints in mev-share
Jonathan Passerat-Palmbach
Sarisht Wadhwa
FedML
214
1
0
19 Aug 2025
Optimal Pure Differentially Private Sparse Histograms in Deterministic Linear Time
Florian Kerschbaum
Steven Lee
Hao Wu
FedML
347
0
0
22 Jul 2025
Quantifying Classifier Utility under Local Differential Privacy
Ye Zheng
Yidan Hu
249
0
0
03 Jul 2025
How to Securely Shuffle? A survey about Secure Shufflers for privacy-preserving computations
Marc Damie
Florian Hahn
Andreas Peter
Jan Ramon
FedML
404
1
0
02 Jul 2025
Dropout-Robust Mechanisms for Differentially Private and Fully Decentralized Mean Estimation
C. Sabater
Sonia Ben Mokhtar
J. Ramon
FedML
266
0
0
04 Jun 2025
Locally Differentially Private Frequency Estimation via Joint Randomized Response
Proceedings on Privacy Enhancing Technologies (PoPETs), 2025
Ye Zheng
Shafizur Rahman Seeam
Yidan Hu
Rui Zhang
Yanchao Zhang
372
2
0
15 May 2025
Differential Privacy for Network Assortativity
Fei Ma
Jinzhi Ouyang
Xincheng Hu
328
0
0
06 May 2025
Towards Trustworthy Federated Learning with Untrusted Participants
Youssef Allouah
R. Guerraoui
John Stephan
FedML
549
7
0
03 May 2025
VDDP: Verifiable Distributed Differential Privacy under the Client-Server-Verifier Setup
Haochen Sun
Xi He
394
1
0
30 Apr 2025
Augmented Shuffle Protocols for Accurate and Robust Frequency Estimation under Differential Privacy
IEEE Symposium on Security and Privacy (S&P), 2025
Takao Murakami
Yuichi Sei
Reo Eriguchi
309
5
0
10 Apr 2025
Infinitely Divisible Noise for Differential Privacy: Nearly Optimal Error in the High
ε
\varepsilon
ε
Regime
Symposium on Foundations of Responsible Computing (FRC), 2025
Charlie Harrison
Pasin Manurangsi
331
0
0
07 Apr 2025
PAUSE: Low-Latency and Privacy-Aware Active User Selection for Federated Learning
Ori Peleg
Natalie Lang
Stefano Rini
Stefano Rini
Nir Shlezinger
Kobi Cohen
FedML
504
0
0
17 Mar 2025
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
International Conference on Learning Representations (ICLR), 2025
Tal Wagner
FedML
357
0
0
21 Feb 2025
Differentially Private Empirical Cumulative Distribution Functions
Antoine Barczewski
Amal Mawass
Jan Ramon
FedML
272
4
0
10 Feb 2025
Segmented Private Data Aggregation in the Multi-message Shuffle Model
Shaowei Wang
Hongqiao Chen
Sufen Zeng
Ruilin Yang
Hui Jiang
...
Kaiqi Yu
Rundong Mei
Shaozheng Huang
Wei Yang
Bangzhou Xin
FedML
465
0
0
31 Dec 2024
Review of Mathematical Optimization in Federated Learning
Shusen Yang
Fangyuan Zhao
Zihao Zhou
Liang Shi
Xuebin Ren
Zongben Xu
FedML
AI4CE
433
6
0
02 Dec 2024
Distributed Differentially Private Data Analytics via Secure Sketching
IACR Cryptology ePrint Archive (IACR ePrint), 2024
Jakob Burkhardt
Hannah Keller
Claudio Orlandi
Chris Schwiegelshohn
FedML
472
1
0
30 Nov 2024
Protection against Source Inference Attacks in Federated Learning using Unary Encoding and Shuffling
Conference on Computer and Communications Security (CCS), 2024
Andreas Athanasiou
Kangsoo Jung
C. Palamidessi
FedML
261
2
0
10 Nov 2024
Differential Privacy on Trust Graphs
Information Technology Convergence and Services (ITCS), 2024
Badih Ghazi
Ravi Kumar
Pasin Manurangsi
Serena Wang
268
1
0
15 Oct 2024
Training on Fake Labels: Mitigating Label Leakage in Split Learning via Secure Dimension Transformation
Yukun Jiang
Peiran Wang
Chengguo Lin
Ziyue Huang
Yong Cheng
357
3
0
11 Oct 2024
Nebula: Efficient, Private and Accurate Histogram Estimation
Ali Shahin Shamsabadi
Peter Snyder
Ralph Giles
A. Bellet
Hamed Haddadi
380
0
0
15 Sep 2024
Locally Private Histograms in All Privacy Regimes
Information Technology Convergence and Services (ITCS), 2024
Clément L. Canonne
Abigail Gentle
496
3
0
09 Aug 2024
Differentially Private Block-wise Gradient Shuffle for Deep Learning
Zilong Zhang
FedML
343
0
0
31 Jul 2024
Weights Shuffling for Improving DPSGD in Transformer-based Models
Jungang Yang
Zhe Ji
Liyao Xiang
331
1
0
22 Jul 2024
Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation
Sajani Vithana
V. Cadambe
Flavio du Pin Calmon
Haewon Jeong
FedML
469
7
0
03 Jul 2024
Efficient Verifiable Differential Privacy with Input Authenticity in the Local and Shuffle Model
Tariq Bontekoe
Hassan Jameel Asghar
Fatih Turkmen
304
8
0
27 Jun 2024
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling
Shaowei Wang
Changyu Dong
Xiangfu Song
Jin Li
Zhili Zhou
Di Wang
Han Wu
604
1
0
26 Jun 2024
On Computing Pairwise Statistics with Local Differential Privacy
Badih Ghazi
Pritish Kamath
Ravi Kumar
Pasin Manurangsi
Adam Sealfon
FedML
299
3
0
24 Jun 2024
RASE: Efficient Privacy-preserving Data Aggregation against Disclosure Attacks for IoTs
Zuyan Wang
Jun Tao
Dikai Zou
190
0
0
31 May 2024
The Privacy Power of Correlated Noise in Decentralized Learning
Youssef Allouah
Anastasia Koloskova
Aymane El Firdoussi
Martin Jaggi
R. Guerraoui
319
19
0
02 May 2024
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
Hilal Asi
Vitaly Feldman
Jelani Nelson
Huy Le Nguyen
Kunal Talwar
Samson Zhou
FedML
379
5
0
16 Apr 2024
Synthesizing Tight Privacy and Accuracy Bounds via Weighted Model Counting
Lisa Oakley
Steven Holtzen
Alina Oprea
397
1
0
26 Feb 2024
Differentially Private Decentralized Learning with Random Walks
International Conference on Machine Learning (ICML), 2024
Edwige Cyffers
A. Bellet
Jalaj Upadhyay
FedML
320
10
0
12 Feb 2024
Lotto: Secure Participant Selection against Adversarial Servers in Federated Learning
Zhifeng Jiang
Peng Ye
Shiqi He
Wei Wang
Ruichuan Chen
Bo Li
424
6
0
05 Jan 2024
A Generalized Shuffle Framework for Privacy Amplification: Strengthening Privacy Guarantees and Enhancing Utility
E. Chen
Yang Cao
Yifei Ge
FedML
339
16
0
22 Dec 2023
Balancing Privacy, Robustness, and Efficiency in Machine Learning
Youssef Allouah
R. Guerraoui
John Stephan
OOD
475
2
0
22 Dec 2023
Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions
AAAI Conference on Artificial Intelligence (AAAI), 2023
T.-H. Hubert Chan
Hao Xie
Mengshi Zhao
276
1
0
14 Dec 2023
Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning
International Symposium on Emerging Information Security and Applications (EISA), 2023
Kangkang Sun
Xiaojin Zhang
Xi Lin
Gaolei Li
Jing Wang
Jianhua Li
196
8
0
30 Nov 2023
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