Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions

3 March 2023

Papers citing "Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions"

7 / 7 papers shown

Title
GANcrop: A Contrastive Defense Against Backdoor Attacks in Federated Learning Xiao-ying Gan Shanyu Gan Taizhi Su Peng Liu FedML 25 0 0 31 May 2024
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 42 19 0 27 Nov 2023
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems Guangjing Wang Ce Zhou Yuanda Wang Bocheng Chen Hanqing Guo Qiben Yan AAML SILM 63 3 0 20 Nov 2023
Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensus Hang Chen Syed Ali Asif Jihong Park Chien-Chung Shen M. Bennis FedML 33 42 0 09 Jan 2021
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 202 434 0 04 Mar 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 188 1,032 0 29 Nov 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017