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FLEDGE: Ledger-based Federated Learning Resilient to Inference and
  Backdoor Attacks

FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks

3 October 2023
Jorge Castillo
Phillip Rieger
Hossein Fereidooni
Qian Chen
Ahmad Sadeghi
    FedML
    AAML
ArXivPDFHTML

Papers citing "FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks"

5 / 5 papers shown
Title
FedCLEAN: byzantine defense by CLustering Errors of Activation maps in Non-IID federated learning environments
FedCLEAN: byzantine defense by CLustering Errors of Activation maps in Non-IID federated learning environments
Mehdi Ben Ghali
R. Bellafqira
G. Coatrieux
AAML
FedML
41
0
0
21 Jan 2025
SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version)
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
43
2
0
11 Jan 2025
Smart Policy Control for Securing Federated Learning Management System
Smart Policy Control for Securing Federated Learning Management System
Aditya Pribadi Kalapaaking
Ibrahim Khalil
Mohammed Atiquzzaman
24
12
0
16 May 2023
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine
  Learning
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning
A. Mondal
Harpreet Virk
Debayan Gupta
30
15
0
06 Feb 2022
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
1