FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning
Attacks in Federated Learning

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning

7 December 2023

Hossein Fereidooni

Alessandro Pegoraro

Phillip Rieger

Alexandra Dmitrienko

Ahmad-Reza Sadeghi

Papers citing "FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning"

5 / 5 papers shown

Title
SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Zhihui Zhao Xiaorong Dong Yimo Ren Jianhua Wang Dan Yu Hongsong Zhu Yongle Chen 82 0 0 24 Feb 2025
Do We Really Need to Design New Byzantine-robust Aggregation Rules? Minghong Fang Seyedsina Nabavirazavi Zhuqing Liu Wei Sun S. Iyengar Haibo Yang AAML OOD 84 6 0 29 Jan 2025
SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Phillip Rieger Alessandro Pegoraro Kavita Kumari Tigist Abera Jonathan Knauer A. Sadeghi AAML 48 2 0 11 Jan 2025
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 117 611 0 27 Dec 2020
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016