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2106.06089
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Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix
International Conference on Machine Learning (ICML), 2021
10 June 2021
Maximilian Lam
Gu-Yeon Wei
David Brooks
Vijay Janapa Reddi
Michael Mitzenmacher
FedML
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Papers citing
"Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix"
43 / 43 papers shown
Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning
Md Fazle Rasul
Alanood Alqobaisi
Bruhadeshwar Bezawada
I. Ray
AAML
FedML
156
0
0
11 Sep 2025
Accelerating Differentially Private Federated Learning via Adaptive Extrapolation
Shokichi Takakura
Seng Pei Liew
Satoshi Hasegawa
FedML
358
1
0
14 Apr 2025
Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates
Chuanyin Wang
Yifei Zhang
Neng Gao
Qiang Luo
FedML
464
2
0
12 Mar 2025
Fed-AugMix: Balancing Privacy and Utility via Data Augmentation
HaoYang Li
Wei Chen
Xiaojin Zhang
FedML
270
0
0
18 Dec 2024
Federated Learning Nodes Can Reconstruct Peers' Image Data
Ethan Wilson
Kai Yue
Chau-Wai Wong
H. Dai
FedML
282
1
0
07 Oct 2024
Privacy Attack in Federated Learning is Not Easy: An Experimental Study
Hangyu Zhu
Liyuan Huang
Zhenping Xie
FedML
263
3
0
28 Sep 2024
FedHide: Federated Learning by Hiding in the Neighbors
European Conference on Computer Vision (ECCV), 2024
Hyunsin Park
Sungrack Yun
FedML
201
0
0
12 Sep 2024
Exploring User-level Gradient Inversion with a Diffusion Prior
Zhuohang Li
Andrew Lowy
Jing Liu
T. Koike-Akino
Bradley Malin
K. Parsons
Ye Wang
DiffM
191
2
0
11 Sep 2024
Analyzing Inference Privacy Risks Through Gradients in Machine Learning
Conference on Computer and Communications Security (CCS), 2024
Zhuohang Li
Andrew Lowy
Jing Liu
T. Koike-Akino
K. Parsons
Bradley Malin
Ye Wang
FedML
293
7
0
29 Aug 2024
Breaking Secure Aggregation: Label Leakage from Aggregated Gradients in Federated Learning
Peng Kuang
Zhiwei Chang
Jiahui Hu
Xiaoyi Pang
Jiacheng Du
Yongle Chen
Kui Ren
FedML
192
10
0
22 Jun 2024
Privacy Preserving Federated Learning in Medical Imaging with Uncertainty Estimation
Nikolas Koutsoubis
Yasin Yilmaz
Ravi P. Ramachandran
M. Schabath
Ghulam Rasool
251
15
0
18 Jun 2024
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives
Linlin Wang
Tianqing Zhu
Wanlei Zhou
Philip S. Yu
241
3
0
16 Jun 2024
Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions
Laiqiao Qin
Tianqing Zhu
Wanlei Zhou
Philip S. Yu
230
18
0
16 Jun 2024
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy
Yichuan Shi
Olivera Kotevska
Viktor Reshniak
Abhishek Singh
Ramesh Raskar
AAML
205
4
0
16 May 2024
Secure Aggregation is Not Private Against Membership Inference Attacks
K. Ngo
Johan Ostman
Giuseppe Durisi
Alexandre Graell i Amat
FedML
382
11
0
26 Mar 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Wenqi Wei
Ling Liu
369
45
0
02 Feb 2024
Survey of Privacy Threats and Countermeasures in Federated Learning
M. Hayashitani
Junki Mori
Isamu Teranishi
FedML
381
2
0
01 Feb 2024
Maximum Knowledge Orthogonality Reconstruction with Gradients in Federated Learning
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023
Feng Wang
Senem Velipasalar
M. C. Gursoy
187
3
0
30 Oct 2023
Kick Bad Guys Out! Conditionally Activated Anomaly Detection in Federated Learning with Zero-Knowledge Proof Verification
Shanshan Han
Wenxuan Wu
Baturalp Buyukates
Weizhao Jin
Qifan Zhang
Yuhang Yao
Salman Avestimehr
Chaoyang He
AAML
495
1
0
06 Oct 2023
SRATTA : Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning
International Conference on Machine Learning (ICML), 2023
Tanguy Marchand
Regis Loeb
Ulysse Marteau-Ferey
Jean Ogier du Terrail
Arthur Pignet
FedML
335
5
0
13 Jun 2023
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning
Kostadin Garov
Dimitar I. Dimitrov
Nikola Jovanović
Martin Vechev
AAML
FedML
540
11
0
05 Jun 2023
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning
International Conference on Machine Learning (ICML), 2023
Junyi Zhu
Ruicong Yao
Matthew B. Blaschko
FedML
292
16
0
31 May 2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility
Xiaojin Zhang
Wenjie Li
Kai Chen
Shutao Xia
Qian Yang
FedML
239
10
0
24 May 2023
Personalized Federated Learning under Mixture of Distributions
International Conference on Machine Learning (ICML), 2023
Yue Wu
Shuaicheng Zhang
Wenchao Yu
Yanchi Liu
Quanquan Gu
Dawei Zhou
Haifeng Chen
Wei Cheng
FedML
265
66
0
01 May 2023
Zero-Knowledge Proof-based Practical Federated Learning on Blockchain
Zhibo Xing
Zijian Zhang
Meng Li
Jing Liu
Liehuang Zhu
Giovanni Russello
M. R. Asghar
213
24
0
12 Apr 2023
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning
Computer Vision and Pattern Recognition (CVPR), 2023
Joshua C. Zhao
A. Elkordy
Atul Sharma
Yahya H. Ezzeldin
A. Avestimehr
S. Bagchi
FedML
147
16
0
27 Mar 2023
LOKI: Large-scale Data Reconstruction Attack against Federated Learning through Model Manipulation
IEEE Symposium on Security and Privacy (IEEE S&P), 2023
Joshua C. Zhao
Atul Sharma
A. Elkordy
Yahya H. Ezzeldin
Salman Avestimehr
S. Bagchi
AAML
FedML
200
56
0
21 Mar 2023
Client-specific Property Inference against Secure Aggregation in Federated Learning
Raouf Kerkouche
G. Ács
Mario Fritz
FedML
272
12
0
07 Mar 2023
Recent Advances on Federated Learning: A Systematic Survey
Neurocomputing (Neurocomputing), 2023
Bingyan Liu
Nuoyan Lv
Yuanchun Guo
Yawen Li
FedML
253
160
0
03 Jan 2023
ScionFL: Efficient and Robust Secure Quantized Aggregation
Y. Ben-Itzhak
Helen Mollering
Benny Pinkas
T. Schneider
Ajith Suresh
Oleksandr Tkachenko
S. Vargaftik
Christian Weinert
Hossein Yalame
Avishay Yanai
231
11
0
13 Oct 2022
Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph
ACM Transactions on Privacy and Security (TOPS), 2022
Yang Lu
Zhengxin Yu
N. Suri
FedML
258
22
0
01 Oct 2022
SNAP: Efficient Extraction of Private Properties with Poisoning
Harsh Chaudhari
John Abascal
Alina Oprea
Matthew Jagielski
Florian Tramèr
Jonathan R. Ullman
MIACV
238
38
0
25 Aug 2022
DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting
IEEE International Conference on Cloud Computing (CLOUD), 2022
Runhua Xu
Nathalie Baracaldo
Yi Zhou
Ali Anwar
S. Kadhe
Heiko Ludwig
FedML
204
26
0
15 Jul 2022
A Survey on Gradient Inversion: Attacks, Defenses and Future Directions
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Rui Zhang
Song Guo
Junxiao Wang
Xin Xie
Dacheng Tao
171
50
0
15 Jun 2022
Gradient Obfuscation Gives a False Sense of Security in Federated Learning
USENIX Security Symposium (USENIX Security), 2022
Kai Yue
Richeng Jin
Chau-Wai Wong
D. Baron
H. Dai
FedML
263
68
0
08 Jun 2022
Generative Adversarial Network Based Synthetic Learning and a Novel Domain Relevant Loss Term for Spine Radiographs
E. Schonfeld
A. Veeravagu
MedIm
98
1
0
05 May 2022
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Nature Communications (Nat Commun), 2022
Sarthak Pati
Ujjwal Baid
Brandon Edwards
Micah J. Sheller
Shih-Han Wang
...
Prashant Shah
Bjoern Menze
J. Barnholtz-Sloan
Jason Martin
Spyridon Bakas
FedML
AI4CE
243
284
0
22 Apr 2022
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning
IEEE Transactions on Dependable and Secure Computing (TDSC), 2022
Georg Pichler
Marco Romanelli
L. Rey Vega
Pablo Piantanida
FedML
141
13
0
30 Mar 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification
International Conference on Machine Learning (ICML), 2022
Yuxin Wen
Jonas Geiping
Liam H. Fowl
Micah Goldblum
Tom Goldstein
FedML
483
111
0
01 Feb 2022
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey
Shangwei Guo
Xu Zhang
Feiyu Yang
Tianwei Zhang
Yan Gan
Tao Xiang
Yang Liu
FedML
239
13
0
19 Dec 2021
Eluding Secure Aggregation in Federated Learning via Model Inconsistency
Conference on Computer and Communications Security (CCS), 2021
Dario Pasquini
Danilo Francati
G. Ateniese
FedML
575
137
0
14 Nov 2021
FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning
Zhifeng Jiang
Wen Wang
Yang Liu
FedML
189
66
0
02 Sep 2021
Federated Learning with Buffered Asynchronous Aggregation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
John Nguyen
Kshitiz Malik
Hongyuan Zhan
Ashkan Yousefpour
Michael G. Rabbat
Mani Malek
Dzmitry Huba
FedML
396
407
0
11 Jun 2021
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