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Auditing Privacy Defenses in Federated Learning via Generative Gradient
  Leakage

Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage

29 March 2022
Zhuohang Li
Jiaxin Zhang
Lu Liu
Jian-Dong Liu
    FedML
ArXivPDFHTML

Papers citing "Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage"

13 / 13 papers shown
Title
Clustering-Based Evolutionary Federated Multiobjective Optimization and Learning
Clustering-Based Evolutionary Federated Multiobjective Optimization and Learning
Chengui Xiao
Songbai Liu
FedML
65
0
0
29 Apr 2025
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling
Kaiyuan Zhang
Siyuan Cheng
Guangyu Shen
Bruno Ribeiro
Shengwei An
Pin-Yu Chen
X. Zhang
Ninghui Li
90
1
0
28 Jan 2025
Gradients Stand-in for Defending Deep Leakage in Federated Learning
Gradients Stand-in for Defending Deep Leakage in Federated Learning
H. Yi
H. Ren
C. Hu
Y. Li
J. Deng
Xin Xie
FedML
25
0
0
11 Oct 2024
Universally Harmonizing Differential Privacy Mechanisms for Federated
  Learning: Boosting Accuracy and Convergence
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence
Shuya Feng
Meisam Mohammady
Hanbin Hong
Shenao Yan
Ashish Kundu
Binghui Wang
Yuan Hong
FedML
36
3
0
20 Jul 2024
Gradient Inversion of Federated Diffusion Models
Gradient Inversion of Federated Diffusion Models
Jiyue Huang
Chi Hong
Lydia Y. Chen
Stefanie Roos
FedML
34
1
0
30 May 2024
DAGER: Exact Gradient Inversion for Large Language Models
DAGER: Exact Gradient Inversion for Large Language Models
Ivo Petrov
Dimitar I. Dimitrov
Maximilian Baader
Mark Niklas Muller
Martin Vechev
FedML
51
3
0
24 May 2024
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated
  AI-enabled Critical Infrastructure
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure
Zehang Deng
Ruoxi Sun
Minhui Xue
Sheng Wen
S. Çamtepe
Surya Nepal
Yang Xiang
35
1
0
24 May 2024
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Sheng Liu
Zihan Wang
Yuxiao Chen
Qi Lei
AAML
MIACV
59
4
0
13 Feb 2024
A Survey on Vulnerability of Federated Learning: A Learning Algorithm
  Perspective
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective
Xianghua Xie
Chen Hu
Hanchi Ren
Jingjing Deng
FedML
AAML
29
19
0
27 Nov 2023
Gradient Leakage Defense with Key-Lock Module for Federated Learning
Gradient Leakage Defense with Key-Lock Module for Federated Learning
Hanchi Ren
Jingjing Deng
Xianghua Xie
Xiaoke Ma
J. Ma
FedML
21
2
0
06 May 2023
Speech Privacy Leakage from Shared Gradients in Distributed Learning
Speech Privacy Leakage from Shared Gradients in Distributed Learning
Zhuohang Li
Jiaxin Zhang
Jian-Dong Liu
FedML
14
1
0
21 Feb 2023
Refiner: Data Refining against Gradient Leakage Attacks in Federated
  Learning
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning
Mingyuan Fan
Cen Chen
Chengyu Wang
Ximeng Liu
Wenmeng Zhou
Jun Huang
AAML
FedML
32
0
0
05 Dec 2022
Analysing Training-Data Leakage from Gradients through Linear Systems
  and Gradient Matching
Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient Matching
Cangxiong Chen
Neill D. F. Campbell
FedML
16
1
0
20 Oct 2022
1