Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2012.06043
Cited By
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective
8 December 2020
Jingwei Sun
Ang Li
Binghui Wang
Huanrui Yang
Hai Li
Yiran Chen
FedML
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
50 / 84 papers shown
Privacy in Federated Learning with Spiking Neural Networks
Dogukan Aksu
Jesus Martinez del Rincon
Ihsen Alouani
AAML
FedML
697
0
0
26 Nov 2025
InfoDecom: Decomposing Information for Defending Against Privacy Leakage in Split Inference
Ruijun Deng
Zhihui Lu
Qiang Duan
122
0
0
17 Nov 2025
SVDefense: Effective Defense against Gradient Inversion Attacks via Singular Value Decomposition
Chenxiang Luo
David K.Y. Yau
Qun Song
AAML
213
0
0
01 Oct 2025
Towards Privacy-Preserving and Heterogeneity-aware Split Federated Learning via Probabilistic Masking
Xingchen Wang
Feijie Wu
Chenglin Miao
Tianchun Li
Haoyu Hu
Qiming Cao
Jing Gao
Lu Su
272
0
0
18 Sep 2025
On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions
Daniel Gutiérrez
Yelizaveta Falkouskaya
Jose L. Hernandez-Ramos
Aris Anagnostopoulos
I. Chatzigiannakis
A. Vitaletti
FedML
260
2
0
19 Aug 2025
Evaluating Selective Encryption Against Gradient Inversion Attacks
Jiajun Gu
Yuhang Yao
Shuaiqi Wang
Carlee Joe-Wong
124
0
0
06 Aug 2025
SelectiveShield: Lightweight Hybrid Defense Against Gradient Leakage in Federated Learning
Borui Li
Li Yan
Jianmin Liu
FedML
161
0
0
06 Aug 2025
DRAUN: An Algorithm-Agnostic Data Reconstruction Attack on Federated Unlearning Systems
Hithem Lamri
Manaar Alam
Haiyan Jiang
Michail Maniatakos
MU
189
0
0
02 Jun 2025
Nosy Layers, Noisy Fixes: Tackling DRAs in Federated Learning Systems using Explainable AI
ACM Asia Conference on Computer and Communications Security (AsiaCCS), 2025
Meghali Nandi
Arash Shaghaghi
Nazatul Haque Sultan
Gustavo Batista
Raymond K. Zhao
Sanjay Jha
AAML
442
0
0
16 May 2025
Improving Efficiency in Federated Learning with Optimized Homomorphic Encryption
Feiran Yang
FedML
324
0
0
03 Apr 2025
Secure Generalization through Stochastic Bidirectional Parameter Updates Using Dual-Gradient Mechanism
Shourya Goel
Himanshi Tibrewal
Anant Jain
Anshul Pundhir
Pravendra Singh
FedML
359
1
0
03 Apr 2025
Defending Against Gradient Inversion Attacks for Biomedical Images via Learnable Data Perturbation
Shiyi Jiang
F. Firouzi
Krishnendu Chakrabarty
AAML
MedIm
272
2
0
19 Mar 2025
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning
Nature Communications (Nat Commun), 2025
Guikun Chen
Xu Zhang
Yue Yang
Yong Liu
Yi Yang
Wenguan Wang
341
0
0
26 Feb 2025
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling
Network and Distributed System Security Symposium (NDSS), 2025
Kaiyuan Zhang
Siyuan Cheng
Guangyu Shen
Bruno Ribeiro
Shengwei An
Pin-Yu Chen
Xinming Zhang
Ninghui Li
833
6
0
28 Jan 2025
Intermediate Outputs Are More Sensitive Than You Think
Tao Huang
Qingyu Huang
Jiayang Meng
AAML
314
1
0
01 Dec 2024
Optimal Defenses Against Gradient Reconstruction Attacks
Yuxiao Chen
Gamze Gürsoy
Qi Lei
FedML
AAML
311
1
0
06 Nov 2024
Gradients Stand-in for Defending Deep Leakage in Federated Learning
H. Yi
H. Ren
C. Hu
Y. Li
J. Deng
Xin Xie
FedML
243
1
0
11 Oct 2024
Federated Learning Nodes Can Reconstruct Peers' Image Data
Ethan Wilson
Kai Yue
Chau-Wai Wong
H. Dai
FedML
338
1
0
07 Oct 2024
Data Poisoning and Leakage Analysis in Federated Learning
Wenqi Wei
Tiansheng Huang
Zachary Yahn
Anoop Singhal
Margaret Loper
Ling Liu
FedML
SILM
260
2
0
19 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
368
9
0
29 Aug 2024
Understanding Data Reconstruction Leakage in Federated Learning from a Theoretical Perspective
Zifan Wang
Binghui Zhang
Meng Pang
Yuan Hong
Binghui Wang
FedML
283
0
0
22 Aug 2024
Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning
Chenfei Nie
Qiang Li
Yuxin Yang
Yuede Ji
Binghui Wang
280
3
0
29 Jul 2024
Non-parametric regularization for class imbalance federated medical image classification
Jeffry Wicaksana
Zengqiang Yan
Kwang-Ting Cheng
FedML
238
3
0
17 Jul 2024
Mjolnir: Breaking the Shield of Perturbation-Protected Gradients via Adaptive Diffusion
Xuan Liu
Siqi Cai
Qihua Zhou
Song Guo
Ruibin Li
Kaiwei Lin
DiffM
AAML
286
0
0
07 Jul 2024
Federated Learning with a Single Shared Image
Sunny Soni
Aaqib Saeed
Yuki M. Asano
FedML
DD
311
3
0
18 Jun 2024
Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients
Weijun Li
Xingliang Yuan
Mark Dras
PILM
308
5
0
03 Jun 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
274
12
0
24 May 2024
Federated Learning with Only Positive Labels by Exploring Label Correlations
Xuming An
Dui Wang
Li Shen
Yong Luo
Han Hu
Bo Du
Yonggang Wen
Dacheng Tao
FedML
283
2
0
24 Apr 2024
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks
Sayedeh Leila Noorbakhsh
Binghui Zhang
Yuan Hong
Binghui Wang
AAML
329
17
0
04 Mar 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Wenqi Wei
Ling Liu
415
54
0
02 Feb 2024
Survey of Privacy Threats and Countermeasures in Federated Learning
M. Hayashitani
Junki Mori
Isamu Teranishi
FedML
418
2
0
01 Feb 2024
Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks
Lulu Xue
Shengshan Hu
Rui-Qing Zhao
Leo Yu Zhang
Shengqing Hu
Lichao Sun
Dezhong Yao
AAML
275
8
0
30 Jan 2024
AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning
Hideaki Takahashi
SILM
319
2
0
29 Dec 2023
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning
AAAI Conference on Artificial Intelligence (AAAI), 2023
Yuting Ma
Yuanzhi Yao
Xiaohua Xu
FedML
206
8
0
16 Dec 2023
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective
Xianghua Xie
Chen Hu
Hanchi Ren
Jingjing Deng
FedML
AAML
301
40
0
27 Nov 2023
OASIS: Offsetting Active Reconstruction Attacks in Federated Learning
IEEE International Conference on Distributed Computing Systems (ICDCS), 2023
Tre' R. Jeter
Truc D. T. Nguyen
Raed Alharbi
My T. Thai
AAML
289
0
0
23 Nov 2023
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
223
3
0
30 Oct 2023
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models
International Conference on Machine Learning (ICML), 2023
Jingwei Sun
Ziyue Xu
Hongxu Yin
Dong Yang
Daguang Xu
Yiran Chen
Holger R. Roth
VLM
291
38
0
02 Oct 2023
PA-iMFL: Communication-Efficient Privacy Amplification Method against Data Reconstruction Attack in Improved Multi-Layer Federated Learning
IEEE Internet of Things Journal (IEEE IoT J.), 2023
Jianhua Wang
Xiaolin Chang
Jelena Mivsić
Vojislav B. Mivsić
Zhi Chen
Junchao Fan
239
7
0
25 Sep 2023
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?
Neural Information Processing Systems (NeurIPS), 2023
Xiaoxiao Sun
Nidham Gazagnadou
Vivek Sharma
Lingjuan Lyu
Hongdong Li
Liang Zheng
327
15
0
22 Sep 2023
Understanding Deep Gradient Leakage via Inversion Influence Functions
Neural Information Processing Systems (NeurIPS), 2023
Haobo Zhang
Junyuan Hong
Yuyang Deng
M. Mahdavi
Jiayu Zhou
FedML
440
13
0
22 Sep 2023
Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks
Daniel Scheliga
Patrick Mäder
M. Seeland
FedML
AAML
366
11
0
08 Sep 2023
Artificial Intelligence for Web 3.0: A Comprehensive Survey
ACM Computing Surveys (ACM Comput. Surv.), 2023
Meng Shen
Zhehui Tan
Dusit Niyato
Yuzhi Liu
Jiawen Kang
Zehui Xiong
Liehuang Zhu
Wei Wang
Xuemin
X. Shen
230
31
0
17 Aug 2023
GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization
IEEE International Conference on Computer Vision (ICCV), 2023
Hao Fang
Bin Chen
Xuan Wang
Zhi Wang
Shutao Xia
319
57
0
09 Aug 2023
On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlook
International Journal of Computer Vision (IJCV), 2023
Mingyuan Fan
Chengyu Wang
Cen Chen
Yang Liu
Jun Huang
HILM
375
14
0
31 Jul 2023
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency
Jiawei Shao
Zijian Li
Wenqiang Sun
Tailin Zhou
Yuchang Sun
Lumin Liu
Zehong Lin
Yuyi Mao
Jun Zhang
FedML
335
46
0
20 Jul 2023
Heterogeneous Federated Learning: State-of-the-art and Research Challenges
ACM Computing Surveys (ACM Comput. Surv.), 2023
Mang Ye
Xiuwen Fang
Bo Du
PongChi Yuen
Dacheng Tao
FedML
AAML
505
521
0
20 Jul 2023
On the Robustness of Split Learning against Adversarial Attacks
European Conference on Artificial Intelligence (ECAI), 2023
Mingyuan Fan
Cen Chen
Chengyu Wang
Wenmeng Zhou
Yanjie Liang
AAML
201
13
0
16 Jul 2023
Temporal Gradient Inversion Attacks with Robust Optimization
IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2023
Bowen Li Jie Li
Hanlin Gu
Ruoxin Chen
Jie Li
Chentao Wu
Na Ruan
Xueming Si
Lixin Fan
AAML
246
6
0
13 Jun 2023
PrivaScissors: Enhance the Privacy of Collaborative Inference through the Lens of Mutual Information
Lin Duan
Jingwei Sun
Yiran Chen
M. Gorlatova
174
5
0
17 May 2023
1
2
Next
Page 1 of 2
