RoFL: Robustness of Secure Federated Learning

RoFL: Robustness of Secure Federated Learning

7 July 2021

Lukas Burkhalter

Alexander Viand

Nicolas Küchler

Papers citing "RoFL: Robustness of Secure Federated Learning"

10 / 10 papers shown

Title
Efficient Full-Stack Private Federated Deep Learning with Post-Quantum Security Yiwei Zhang R. Behnia A. Yavuz Reza Ebrahimi E. Bertino FedML 31 0 0 09 May 2025
TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning Runhua Xu Bo Li Chao Li J. Joshi Shuai Ma Jianxin Li FedML 41 10 0 10 Jan 2025
FLIPS: Federated Learning using Intelligent Participant Selection R. Bhope K. R. Jayaram N. Venkatasubramanian Ashish Verma Gegi Thomas FedML 29 3 0 07 Aug 2023
FLAD: Adaptive Federated Learning for DDoS Attack Detection Roberto Doriguzzi-Corin Domenico Siracusa FedML 36 61 0 13 May 2022
When the Curious Abandon Honesty: Federated Learning Is Not Private Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 69 181 0 06 Dec 2021
Lightweight Techniques for Private Heavy Hitters Dan Boneh Elette Boyle Henry Corrigan-Gibbs N. Gilboa Yuval Ishai 26 105 0 29 Dec 2020
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 290 1,815 0 14 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 1,707 0 18 Mar 2020
Model-Reuse Attacks on Deep Learning Systems Yujie Ji Xinyang Zhang S. Ji Xiapu Luo Ting Wang SILM AAML 134 186 0 02 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,032 0 29 Nov 2018