Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning

27 April 2020

Papers citing "Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning"

8 / 8 papers shown

Title
Trustworthy Federated Learning: Privacy, Security, and Beyond Chunlu Chen Ji Liu Haowen Tan Xingjian Li Kevin I-Kai Wang Peng Li Kouichi Sakurai Dejing Dou FedML 28 1 0 03 Nov 2024
Federated Learning: Attacks, Defenses, Opportunities, and Challenges Ghazaleh Shirvani Saeid Ghasemshirazi Behzad Beigzadeh FedML 24 3 0 10 Mar 2024
Expressive variational quantum circuits provide inherent privacy in federated learning Niraj Kumar Jamie Heredge Changhao Li Shaltiel Eloul Shree Hari Sureshbabu Marco Pistoia FedML 22 8 0 22 Sep 2023
Mitigating Cross-client GANs-based Attack in Federated Learning Hong Huang Xinyu Lei Tao Xiang AAML 11 1 0 25 Jul 2023
On the Security & Privacy in Federated Learning Gorka Abad S. Picek Víctor Julio Ramírez-Durán A. Urbieta 14 11 0 10 Dec 2021
A Fusion-Denoising Attack on InstaHide with Data Augmentation Xinjian Luo X. Xiao Yuncheng Wu Juncheng Liu Beng Chin Ooi FedML PICV 16 7 0 17 May 2021
From Distributed Machine Learning to Federated Learning: A Survey Ji Liu Jizhou Huang Yang Zhou Xuhong Li Shilei Ji Haoyi Xiong Dejing Dou FedML OOD 18 236 0 29 Apr 2021
Constructing Unrestricted Adversarial Examples with Generative Models Yang Song Rui Shu Nate Kushman Stefano Ermon GAN AAML 150 276 0 21 May 2018