Learning-to-Attack-Federated-Learning

Federated Learning Attacker Framework

An implementation of a framework for learning how to attack federated learning systems

GitHub

15 stars
1 watching
5 forks
Language: Python
last commit: about 2 years ago

Related projects:

Repository Description Stars
hfzhang31/a3fl A framework for attacking federated learning systems with adaptive backdoor attacks 22
ebagdasa/backdoor_federated_learning An implementation of a framework for backdoors in federated learning, allowing researchers to test and analyze various attacks on distributed machine learning models. 271
ksreenivasan/ood_federated_learning Researchers investigate vulnerabilities in Federated Learning systems by introducing new backdoor attacks and exploring methods to defend against them. 64
jeremy313/fl-wbc A defense mechanism against model poisoning attacks in federated learning 37
ai-secure/crfl This project presents a framework for robust federated learning against backdoor attacks. 71
eth-sri/bayes-framework-leakage Develops and evaluates a framework for detecting attacks on federated learning systems 11
aiot-mlsys-lab/fedrolex An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources. 61
deu30303/feddefender A PyTorch implementation of an attack-tolerant federated learning system to train robust local models against malicious attacks from adversaries. 9
xtra-computing/fedov Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models. 14
fangxiuwen/robust_fl An implementation of a robust federated learning framework for handling noisy and heterogeneous clients in machine learning. 41
lins-lab/fedbr An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data 25
ai-secure/dba A tool for demonstrating and analyzing attacks on federated learning systems by introducing backdoors into distributed machine learning models. 176
haozzh/fedcr Evaluates various methods for federated learning on different models and tasks. 17
jeremy313/soteria An implementation of a defense against model inversion attacks in federated learning 55
xtra-computing/fedsim A framework that enables federated learning across multiple datasets while optimizing model performance with record similarities. 24