Gradient Inversion with Generative Image Prior

28 October 2021

Jaechang Kim

Jungseul Ok

Papers citing "Gradient Inversion with Generative Image Prior"

27 / 27 papers shown

Title
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 97 1 0 28 Jan 2025
NET-SA: An Efficient Secure Aggregation Architecture Based on In-Network Computing Qingqing Ren Wen Wang Shuyong Zhu Zhiyuan Wu Yujun Zhang 35 0 0 02 Jan 2025
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
Gradient Inversion of Federated Diffusion Models Jiyue Huang Chi Hong Lydia Y. Chen Stefanie Roos FedML 34 1 0 30 May 2024
Data Reconstruction Attacks and Defenses: A Systematic Evaluation Sheng Liu Zihan Wang Yuxiao Chen Qi Lei AAML MIACV 59 4 0 13 Feb 2024
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off Yuecheng Li Lele Fu Tong Wang Jian Lou Bin Chen Lei Yang Zibin Zheng Zibin Zheng Chuan Chen FedML 70 4 0 10 Feb 2024
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
Approximate and Weighted Data Reconstruction Attack in Federated Learning Yongcun Song Ziqi Wang Enrique Zuazua AAML FedML 22 4 0 13 Aug 2023
Gradient Leakage Defense with Key-Lock Module for Federated Learning Hanchi Ren Jingjing Deng Xianghua Xie Xiaoke Ma J. Ma FedML 24 2 0 06 May 2023
Bounding Training Data Reconstruction in DP-SGD Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 33 39 0 14 Feb 2023
Dataset Distillation: A Comprehensive Review Ruonan Yu Songhua Liu Xinchao Wang DD 41 121 0 17 Jan 2023
Reconstructing Training Data from Model Gradient, Provably Zihan Wang Jason D. Lee Qi Lei FedML 22 24 0 07 Dec 2022
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning Mingyuan Fan Cen Chen Chengyu Wang Ximeng Liu Wenmeng Zhou Jun Huang AAML FedML 34 0 0 05 Dec 2022
DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics Renjie Pi Weizhong Zhang Yueqi Xie Jiahui Gao Xiaoyu Wang Sunghun Kim Qifeng Chen DD 39 26 0 20 Nov 2022
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning Samuel Maddock Alexandre Sablayrolles Pierre Stock FedML 12 22 0 06 Oct 2022
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis Sanjay Kariyappa Chuan Guo Kiwan Maeng Wenjie Xiong G. E. Suh Moinuddin K. Qureshi Hsien-Hsin S. Lee FedML 13 29 0 12 Sep 2022
Dropout is NOT All You Need to Prevent Gradient Leakage Daniel Scheliga Patrick Mäder M. Seeland FedML 22 12 0 12 Aug 2022
Gradient Obfuscation Gives a False Sense of Security in Federated Learning Kai Yue Richeng Jin Chau-Wai Wong D. Baron H. Dai FedML 28 46 0 08 Jun 2022
Few-Shot Unlearning by Model Inversion Youngsik Yoon Jinhwan Nam Hyojeong Yun Jaeho Lee Dongwoo Kim Jungseul Ok MU 20 17 0 31 May 2022
Recovering Private Text in Federated Learning of Language Models Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 25 74 0 17 May 2022
AGIC: Approximate Gradient Inversion Attack on Federated Learning Jin Xu Chi Hong Jiyue Huang L. Chen Jérémie Decouchant AAML FedML 16 21 0 28 Apr 2022
TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data Isha Garg M. Nagaraj Kaushik Roy FedML 21 1 0 21 Jan 2022
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 19 41 0 08 Nov 2021
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models Liam H. Fowl Jonas Geiping W. Czaja Micah Goldblum Tom Goldstein FedML 21 144 0 25 Oct 2021
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 168 787 0 15 Feb 2021
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 279 10,348 0 12 Dec 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 317 11,681 0 09 Mar 2017