Lockdown
Federated Learning Defender
A backdoor defense system against attacks in federated learning algorithms used for machine learning model training on distributed datasets.
A backdoor defense for federated learning via isolated subspace training (NeurIPS2023)
14 stars
4 watching
0 forks
Language: Python
last commit: 11 months ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 ai-secure/fedgame | An implementation of a game-theoretic defense against backdoor attacks in federated learning. | 5 |
 jeremy313/soteria | An implementation of a defense against model inversion attacks in federated learning | 55 |
 dcalab-unipv/turning-privacy-preserving-mechanisms-against-federated-learning | This project presents an attack on federated learning systems to compromise their privacy-preserving mechanisms. | 8 |
| ai-secure/dba | A tool for demonstrating and analyzing attacks on federated learning systems by introducing backdoors into distributed machine learning models. | 177 |
 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 |
 jhcknzzm/federated-learning-backdoor | An implementation of a federated learning attack method known as Neurotoxin, which introduces backdoors into machine learning models during the training process. | 63 |
| jeremy313/fl-wbc | A defense mechanism against model poisoning attacks in federated learning | 37 |
 eth-sri/bayes-framework-leakage | Develops and evaluates a framework for detecting attacks on federated learning systems | 11 |
 deu30303/feddefender | A PyTorch implementation of an attack-tolerant federated learning system to train robust local models against malicious attacks from adversaries. | 9 |
 hfzhang31/a3fl | A framework for attacking federated learning systems with adaptive backdoor attacks | 22 |
 zju-diver/shapleyfl-robust-federated-learning-based-on-shapley-value | An implementation of a robust federated learning method based on Shapley value to defend against various data and model poisoning attacks | 19 |
 ksreenivasan/ood_federated_learning | Researchers investigate vulnerabilities in Federated Learning systems by introducing new backdoor attacks and exploring methods to defend against them. | 64 |
| git-disl/stdlens | A framework designed to protect federated learning models from hijacking attacks by identifying and removing compromised client gradients | 7 |
| ai-secure/crfl | This project presents a framework for robust federated learning against backdoor attacks. | 71 |
 wizard1203/vhl | A toolkit for federated learning with a focus on defending against data heterogeneity | 40 |