FedCC: Robust Federated Learning against Model Poisoning Attacks

20 February 2025

Papers citing "FedCC: Robust Federated Learning against Model Poisoning Attacks"

7 / 7 papers shown

Title
MultiConfederated Learning: Inclusive Non-IID Data handling with Decentralized Federated Learning Michael Duchesne Kaiwen Zhang Talhi Chamseddine FedML 32 0 0 20 Apr 2024
Fedward: Flexible Federated Backdoor Defense Framework with Non-IID Data Zekai Chen Fuyi Wang Zhiwei Zheng Ximeng Liu Yujie Lin FedML AAML 22 3 0 01 Jul 2023
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications Ali Raza Shujun Li K. Tran L. Koehl Kim Duc Tran AAML 25 3 0 18 Jul 2022
CalFAT: Calibrated Federated Adversarial Training with Label Skewness Chen Chen Yuchen Liu Xingjun Ma Lingjuan Lyu FedML 164 32 0 30 May 2022
Federated Learning on Non-IID Data Silos: An Experimental Study Q. Li Yiqun Diao Quan Chen Bingsheng He FedML OOD 87 946 0 03 Feb 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 108 611 0 27 Dec 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 179 1,032 0 29 Nov 2018