MPAF: Model Poisoning Attacks to Federated Learning based on Fake Clients

16 March 2022

Papers citing "MPAF: Model Poisoning Attacks to Federated Learning based on Fake Clients"

6 / 56 papers shown

Title
FLCert: Provably Secure Federated Learning against Poisoning Attacks Xiaoyu Cao Zaixi Zhang Jinyuan Jia Neil Zhenqiang Gong FedML OOD 83 59 0 02 Oct 2022
FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients Zaixi Zhang Xiaoyu Cao Jin Jia Neil Zhenqiang Gong AAML FedML 24 214 0 19 Jul 2022
Blades: A Unified Benchmark Suite for Byzantine Attacks and Defenses in Federated Learning Shenghui Li Edith C.H. Ngai Fanghua Ye Li Ju Tianru Zhang Thiemo Voigt AAML FedML 32 12 0 10 Jun 2022
PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning Hongbin Liu Jinyuan Jia Neil Zhenqiang Gong 25 34 0 13 May 2022
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 117 612 0 27 Dec 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,032 0 29 Nov 2018