federated-fdp
Private FL framework
A framework for private federated learning that provides differential privacy guarantees at the individual record level.
7 stars
1 watching
0 forks
Language: Python
last commit: over 3 years ago Related projects:
Repository | Description | Stars |
---|---|---|
shenzebang/centaur-privacy-federated-representation-learning | A framework for Federated Learning with Differential Privacy using PyTorch | 13 |
kenziyuliu/private-cross-silo-fl | This repository provides an implementation of a cross-silo federated learning framework with differential privacy mechanisms. | 25 |
ganyuwang/vfl-czofo | A unified framework for improving privacy and reducing communication overhead in distributed machine learning models. | 12 |
securefederatedai/openfl | A Python framework for collaborative machine learning without sharing sensitive data | 738 |
cuis15/fcfl | An implementation of Fair and Consistent Federated Learning using Python. | 20 |
jeremy313/soteria | An implementation of a defense against model inversion attacks in federated learning | 55 |
rong-dai/dispfl | An implementation of a personalized federated learning framework with decentralized sparse training and peer-to-peer communication protocol. | 72 |
sap-samples/machine-learning-diff-private-federated-learning | Simulates a federated learning setting to preserve individual data privacy | 365 |
xiyuanyang45/dynamicpfl | A method for personalizing machine learning models in federated learning settings with adaptive differential privacy to improve performance and robustness | 57 |
substra/substra | Enables the training and validation of machine learning models on distributed datasets in a secure and scalable manner. | 274 |
bdemo/pfedbred_public | A project that proposes a novel federated learning approach to address the issue of incomplete information in personalized machine learning models | 9 |
shenzebang/federated-learning-pytorch | A PyTorch-based framework for Federated Learning experiments | 40 |
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 |
git-disl/lockdown | A backdoor defense system for federated learning, designed to protect against data poisoning attacks by isolating subspace training and aggregating models with robust consensus fusion. | 18 |
omarfoq/fedem | Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. | 157 |