Towards General Deep Leakage in Federated Learning

Towards General Deep Leakage in Federated Learning

18 October 2021

Papers citing "Towards General Deep Leakage in Federated Learning"

9 / 9 papers shown

Title
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
FedMultimodal: A Benchmark For Multimodal Federated Learning Tiantian Feng Digbalay Bose Tuo Zhang Rajat Hebbar Anil Ramakrishna Rahul Gupta Mi Zhang Salman Avestimehr Shrikanth Narayanan 32 48 0 15 Jun 2023
A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness Zongxiong Chen Jiahui Geng Derui Zhu Herbert Woisetschlaeger Qing Li Sonja Schimmler Ruben Mayer Chunming Rong DD 24 9 0 05 May 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 35 12 0 27 Mar 2023
AI Models Close to your Chest: Robust Federated Learning Strategies for Multi-site CT Edward H. Lee B. Kelly E. Altinmakas H. Doğan M. Mohammadzadeh ... Faezeh Sazgara S. Wong Michael E. Moseley S. Halabi Kristen W. Yeom FedML OOD 15 1 0 23 Mar 2023
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
User-Level Differential Privacy against Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Tiantian Feng Raghuveer Peri Shrikanth Narayanan FedML 13 28 0 05 Apr 2022
Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Settings Tiantian Feng H. Hashemi Rajat Hebbar M. Annavaram Shrikanth S. Narayanan 13 25 0 26 Dec 2021
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 19 41 0 08 Nov 2021