robbing_the_fed
Model inversion attack
This implementation allows an attacker to directly obtain user data from federated learning gradient updates by modifying the shared model architecture.
23 stars
2 watching
5 forks
Language: Python
last commit: almost 3 years ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 hfzhang31/a3fl | A framework for attacking federated learning systems with adaptive backdoor attacks | 22 |
 inspire-group/modelpoisoning | An implementation of model poisoning attacks in federated learning | 146 |
 ml-postech/gradient-inversion-generative-image-prior | An implementation of a method to invert gradients in federated learning to potentially reveal sensitive client data | 39 |
 sliencerx/learning-to-attack-federated-learning | An implementation of a framework for learning how to attack federated learning systems | 15 |
 eth-sri/bayes-framework-leakage | Develops and evaluates a framework for detecting attacks on federated learning systems | 11 |
 jeremy313/fl-wbc | A defense mechanism against model poisoning attacks in federated learning | 37 |
| jeremy313/soteria | An implementation of a defense against model inversion attacks in federated learning | 55 |
 gwenlegate/guidinglastlayerflpretrain | Investigates transfer learning in federated learning by guiding the last layer with pre-trained models | 7 |
 zhuohangli/ggl | An attack implementation to test and evaluate the effectiveness of federated learning privacy defenses. | 57 |
 ksreenivasan/ood_federated_learning | Researchers investigate vulnerabilities in Federated Learning systems by introducing new backdoor attacks and exploring methods to defend against them. | 64 |
 jonasgeiping/breaching | A PyTorch framework for analyzing vulnerabilities in federated learning models and predicting data breaches | 269 |
 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 |
 gdisag/gradient_disaggregation | An algorithm that breaks secure aggregation protocols in federated learning by recovering individual model updates from aggregated sums | 14 |
 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 |
 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 |