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EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in
  Federated Learning

EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning

2 October 2024
Syed Irfan Ali Meerza
Jian-Dong Liu
ArXivPDFHTML

Papers citing "EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning"

4 / 4 papers shown
Title
DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks
  in Federated Learning
DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks in Federated Learning
Md Tamjid Hossain
Shafkat Islam
S. Badsha
Haoting Shen
AAML
48
41
0
21 Sep 2021
Enforcing fairness in private federated learning via the modified method
  of differential multipliers
Enforcing fairness in private federated learning via the modified method of differential multipliers
Borja Rodríguez Gálvez
Filip Granqvist
Rogier van Dalen
M. Seigel
FedML
36
51
0
17 Sep 2021
FedFair: Training Fair Models In Cross-Silo Federated Learning
FedFair: Training Fair Models In Cross-Silo Federated Learning
Lingyang Chu
Lanjun Wang
Yanjie Dong
J. Pei
Zirui Zhou
Yong Zhang
FedML
56
40
0
13 Sep 2021
Analyzing Federated Learning through an Adversarial Lens
Analyzing Federated Learning through an Adversarial Lens
A. Bhagoji
Supriyo Chakraborty
Prateek Mittal
S. Calo
FedML
177
1,014
0
29 Nov 2018
1