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2001.02610
Cited By
iDLG: Improved Deep Leakage from Gradients
8 January 2020
Bo Zhao
Konda Reddy Mopuri
Hakan Bilen
FedML
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Papers citing
"iDLG: Improved Deep Leakage from Gradients"
50 / 334 papers shown
Title
Privacy Attack in Federated Learning is Not Easy: An Experimental Study
Hangyu Zhu
Liyuan Huang
Zhenping Xie
FedML
85
1
0
28 Sep 2024
In-depth Analysis of Privacy Threats in Federated Learning for Medical Data
B. Das
M. H. Amini
Yanzhao Wu
61
0
0
27 Sep 2024
Federated Learning under Attack: Improving Gradient Inversion for Batch of Images
Luiz Leite
Yuri Santo
Bruno L. Dalmazo
André Riker
FedML
44
5
0
26 Sep 2024
Perfect Gradient Inversion in Federated Learning: A New Paradigm from the Hidden Subset Sum Problem
Qiongxiu Li
Lixia Luo
Agnese Gini
Changlong Ji
Zhanhao Hu
Xiao-Li Li
Chengfang Fang
Jie Shi
Xiaolin Hu
FedML
85
3
0
21 Sep 2024
Data Poisoning and Leakage Analysis in Federated Learning
Wenqi Wei
Tiansheng Huang
Zachary Yahn
Anoop Singhal
Margaret Loper
Ling Liu
FedML
SILM
88
0
0
19 Sep 2024
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework
Zilinghan Li
Shilan He
Ze Yang
Minseok Ryu
Kibaek Kim
Ravi K. Madduri
FedML
225
16
0
17 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
91
1
0
11 Sep 2024
S
2
S^2
S
2
NeRF: Privacy-preserving Training Framework for NeRF
Bokang Zhang
Yanglin Zhang
Zhikun Zhang
Jinglan Yang
Lingying Huang
Junfeng Wu
123
2
0
03 Sep 2024
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism
Xiaoyan Yu
Yifan Wei
Pu Li
Shuaishuai Zhou
Hao Peng
Li Sun
Liehuang Zhu
Philip S. Yu
FedML
122
2
0
01 Sep 2024
Understanding Data Reconstruction Leakage in Federated Learning from a Theoretical Perspective
Zifan Wang
Binghui Zhang
Meng Pang
Yuan Hong
Binghui Wang
FedML
116
0
0
22 Aug 2024
Random Gradient Masking as a Defensive Measure to Deep Leakage in Federated Learning
Joon Kim
Sejin Park
AAML
FedML
123
2
0
15 Aug 2024
Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning
Chenfei Nie
Qiang Li
Yuxin Yang
Yuede Ji
Binghui Wang
116
1
0
29 Jul 2024
MedLeak: Multimodal Medical Data Leakage in Secure Federated Learning with Crafted Models
Shanghao Shi
Md Shahedul Haque
Abhijeet Parida
Chaoyu Zhang
M. Linguraru
Y. T. Hou
Syed Muhammad Anwar
W. Lou
FedML
112
4
0
13 Jul 2024
Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization
Wenrui Yu
Qiongxiu Li
Milan Lopuhaä-Zwakenberg
Mads Græsbøll Christensen
Richard Heusdens
FedML
104
4
0
12 Jul 2024
Enhancing Privacy of Spatiotemporal Federated Learning against Gradient Inversion Attacks
Lele Zheng
Yang Cao
Renhe Jiang
Kenjiro Taura
Yulong Shen
Sheng Li
Masatoshi Yoshikawa
AAML
110
3
0
11 Jul 2024
QBI: Quantile-based Bias Initialization for Efficient Private Data Reconstruction in Federated Learning
Micha V. Nowak
Tim P. Bott
David Khachaturov
Frank Puppe
Adrian Krenzer
Amar Hekalo
FedML
89
1
0
26 Jun 2024
Machine Unlearning with Minimal Gradient Dependence for High Unlearning Ratios
Tao Huang
Ziyang Chen
Jiayang Meng
Qingyu Huang
Xu Yang
Xun Yi
Ibrahim Khalil
MU
81
0
0
24 Jun 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
91
5
0
22 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
95
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
119
9
0
16 Jun 2024
Is Diffusion Model Safe? Severe Data Leakage via Gradient-Guided Diffusion Model
Jiayang Meng
Tao Huang
Hong Chen
Cuiping Li
DiffM
82
1
0
13 Jun 2024
R-CONV: An Analytical Approach for Efficient Data Reconstruction via Convolutional Gradients
T. Eltaras
Q. Malluhi
Alessandro Savino
S. Di Carlo
Adnan Qayyum
Junaid Qadir
FedML
70
1
0
06 Jun 2024
Inference Attacks: A Taxonomy, Survey, and Promising Directions
Feng Wu
Lei Cui
Shaowen Yao
Shui Yu
152
2
0
04 Jun 2024
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
Zhibo Xing
Zijian Zhang
Ziáng Zhang
Jiamou Liu
Liehuang Zhu
Giovanni Russello
FedML
118
3
0
03 Jun 2024
Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients
Weijun Li
Xingliang Yuan
Mark Dras
PILM
106
3
0
03 Jun 2024
Amalgam: A Framework for Obfuscated Neural Network Training on the Cloud
Sifat Ut Taki
Spyridon Mastorakis
FedML
116
1
0
02 Jun 2024
Gradient Inversion of Federated Diffusion Models
Jiyue Huang
Chi Hong
Lydia Y. Chen
Stefanie Roos
FedML
90
1
0
30 May 2024
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
Martín Bertrán
Shuai Tang
Michael Kearns
Jamie Morgenstern
Aaron Roth
Zhiwei Steven Wu
AAML
115
19
0
30 May 2024
Enhancing Security and Privacy in Federated Learning using Low-Dimensional Update Representation and Proximity-Based Defense
Wenjie Li
K. Fan
Jingyuan Zhang
Hui Li
Wei Yang Bryan Lim
Qiang Yang
AAML
FedML
103
0
0
29 May 2024
DAGER: Exact Gradient Inversion for Large Language Models
Ivo Petrov
Dimitar I. Dimitrov
Maximilian Baader
Mark Niklas Muller
Martin Vechev
FedML
113
7
0
24 May 2024
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
103
3
0
24 May 2024
Federated Learning in Healthcare: Model Misconducts, Security, Challenges, Applications, and Future Research Directions -- A Systematic Review
Md. Shahin Ali
M. Ahsan
Lamia Tasnim
Sadia Afrin
Koushik Biswas
Maruf Md. Sajjad Hossain
Md Mahfuz Ahmed
Ronok Hashan
Md. Khairul Islam
Shivakumar Raman
102
13
0
22 May 2024
Information Leakage from Embedding in Large Language Models
Zhipeng Wan
Anda Cheng
Yinggui Wang
Lei Wang
PILM
101
5
0
20 May 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
92
3
0
16 May 2024
Feature-based Federated Transfer Learning: Communication Efficiency, Robustness and Privacy
Feng Wang
M. C. Gursoy
Senem Velipasalar
103
0
0
15 May 2024
Prospects of Privacy Advantage in Quantum Machine Learning
Jamie Heredge
Niraj Kumar
Dylan Herman
Shouvanik Chakrabarti
Romina Yalovetzky
Shree Hari Sureshbabu
Changhao Li
Marco Pistoia
120
7
0
14 May 2024
A Survey on Privacy-Preserving Caching at Network Edge: Classification, Solutions, and Challenges
Xianzhi Zhang
Yipeng Zhou
Di Wu
Shazia Riaz
Quan Z. Sheng
Di Wu
Linchang Xiao
55
6
0
03 May 2024
Recovering Labels from Local Updates in Federated Learning
Huancheng Chen
H. Vikalo
FedML
AAML
55
5
0
02 May 2024
Advances and Open Challenges in Federated Learning with Foundation Models
Chao Ren
Han Yu
Hongyi Peng
Xiaoli Tang
Anran Li
...
A. Tan
Bo Zhao
Xiaoxiao Li
Zengxiang Li
Qiang Yang
FedML
AIFin
AI4CE
182
20
0
23 Apr 2024
Beyond Noise: Privacy-Preserving Decentralized Learning with Virtual Nodes
Sayan Biswas
Mathieu Even
Anne-Marie Kermarrec
Laurent Massoulie
Rafael Pires
Rishi Sharma
M. Vos
96
4
0
15 Apr 2024
On the Efficiency of Privacy Attacks in Federated Learning
Nawrin Tabassum
Ka-Ho Chow
Xuyu Wang
Wenbin Zhang
Yanzhao Wu
FedML
75
3
0
15 Apr 2024
You Can Use But Cannot Recognize: Preserving Visual Privacy in Deep Neural Networks
Qiushi Li
Yan Zhang
Ju Ren
Qi Li
Yaoxue Zhang
AAML
PICV
106
26
0
05 Apr 2024
Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning
Hongsheng Hu
Shuo Wang
Tian Dong
Minhui Xue
AAML
105
39
0
04 Apr 2024
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning
Joshua C. Zhao
Ahaan Dabholkar
Atul Sharma
Saurabh Bagchi
FedML
81
3
0
26 Mar 2024
Enabling Privacy-preserving Model Evaluation in Federated Learning via Fully Homomorphic Encryption
Cem Ata Baykara
Ali Burak Ünal
Mete Akgün
FedML
55
0
0
21 Mar 2024
Efficient and Privacy-Preserving Federated Learning based on Full Homomorphic Encryption
Yuqi Guo
Lin Li
Zhongxiang Zheng
Hanrui Yun
Ruoyan Zhang
Xiaolin Chang
Zhixuan Gao
FedML
54
4
0
18 Mar 2024
Pencil: Private and Extensible Collaborative Learning without the Non-Colluding Assumption
Xuanqi Liu
Zhuotao Liu
Qi Li
Ke Xu
Mingwei Xu
90
9
0
17 Mar 2024
Adaptive Hybrid Masking Strategy for Privacy-Preserving Face Recognition Against Model Inversion Attack
Yinggui Wang
Yuanqing Huang
Jianshu Li
Le Yang
Kai Song
Lei Wang
AAML
PICV
118
1
0
14 Mar 2024
RAF-GI: Towards Robust, Accurate and Fast-Convergent Gradient Inversion Attack in Federated Learning
Can Liu
Jin Wang
Dong-Yang Yu
AAML
47
1
0
13 Mar 2024
MGIC: A Multi-Label Gradient Inversion Attack based on Canny Edge Detection on Federated Learning
Can Liu
Jin Wang
130
1
0
13 Mar 2024
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