Fishing for User Data in Large-Batch Federated Learning via Gradient
Magnification

Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

1 February 2022

Papers citing "Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification"

15 / 15 papers shown

Title
ReCIT: Reconstructing Full Private Data from Gradient in Parameter-Efficient Fine-Tuning of Large Language Models Jin Xie Ruishi He Songze Li Xiaojun Jia Shouling Ji SILM AAML 66 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 100 1 0 28 Jan 2025
Attribute Inference Attacks for Federated Regression Tasks Francesco Diana Othmane Marfoq Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML 175 1 0 19 Nov 2024
DAGER: Exact Gradient Inversion for Large Language Models Ivo Petrov Dimitar I. Dimitrov Maximilian Baader Mark Niklas Muller Martin Vechev FedML 55 3 0 24 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
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 38 13 0 27 Jul 2023
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses G. Buzaglo Niv Haim Gilad Yehudai Gal Vardi Yakir Oz Yaniv Nikankin Michal Irani 31 10 0 04 Jul 2023
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning Joshua C. Zhao A. Elkordy Atul Sharma Yahya H. Ezzeldin A. Avestimehr S. Bagchi FedML 37 12 0 27 Mar 2023
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning Samuel Maddock Alexandre Sablayrolles Pierre Stock FedML 12 22 0 06 Oct 2022
Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph Yang Lu Zhengxin Yu N. Suri FedML 24 14 0 01 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
On Privacy and Personalization in Cross-Silo Federated Learning Ziyu Liu Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 22 51 0 16 Jun 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
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets Florian Tramèr Reza Shokri Ayrton San Joaquin Hoang Minh Le Matthew Jagielski Sanghyun Hong Nicholas Carlini MIACV 36 106 0 31 Mar 2022
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning Shaoxiong Ji Yue Tan Teemu Saravirta Zhiqin Yang Yixin Liu Lauri Vasankari Shirui Pan Guodong Long A. Walid FedML 37 76 0 25 Feb 2021