PrivacyFL: A simulator for privacy-preserving and secure federated learning

19 February 2020

Papers citing "PrivacyFL: A simulator for privacy-preserving and secure federated learning"

6 / 6 papers shown

Title
Evaluating the Potential of Federated Learning for Maize Leaf Disease Prediction Thalita Mendonça Antico Larissa F. Rodrigues Moreira Rodrigo Moreira 103 24 0 10 Dec 2024
Vertical Federated Learning: Taxonomies, Threats, and Prospects Qun Li Chandra Thapa Lawrence Ong Yifeng Zheng Hua Ma S. Çamtepe Anmin Fu Yan Gao FedML 36 10 0 03 Feb 2023
Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions A. Rauniyar D. Hagos Debesh Jha J. E. Haakegaard Ulas Bagci D. Rawat Vladimir Vlassov OOD 41 91 0 05 Aug 2022
MUD-PQFed: Towards Malicious User Detection in Privacy-Preserving Quantized Federated Learning Hua Ma Qun Li Yifeng Zheng Zhi Zhang Xiaoning Liu Yan Gao S. Al-Sarawi Derek Abbott FedML 21 3 0 19 Jul 2022
Protea: Client Profiling within Federated Systems using Flower Wanru Zhao Xinchi Qiu Javier Fernandez-Marques Pedro Porto Buarque de Gusmão Nicholas D. Lane 27 6 0 03 Jul 2022
SecFL: Confidential Federated Learning using TEEs D. Quoc Christof Fetzer FedML 16 16 0 03 Oct 2021