Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations

6 June 2023

Papers citing "Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations"

5 / 5 papers shown

Title
secureTF: A Secure TensorFlow Framework D. Quoc Franz Gregor Sergei Arnautov Roland Kunkel Pramod Bhatotia Christof Fetzer 44 40 0 20 Jan 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 102 595 0 27 Dec 2020
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 174 1,690 0 18 Mar 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 177 1,014 0 29 Nov 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 112 391 0 08 Jun 2018