STDLens
Gradient protector
A framework designed to protect federated learning models from hijacking attacks by identifying and removing compromised client gradients
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last commit: over 1 year ago Related projects:
Repository | Description | Stars |
---|---|---|
git-disl/lockdown | A backdoor defense system against attacks in federated learning algorithms used for machine learning model training on distributed datasets. | 14 |
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lhfowl/robbing_the_fed | This implementation allows an attacker to directly obtain user data from federated learning gradient updates by modifying the shared model architecture. | 23 |
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gdisag/gradient_disaggregation | An algorithm that breaks secure aggregation protocols in federated learning by recovering individual model updates from aggregated sums | 14 |
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dmlc/xgboost.jl | A Julia package implementing a distributed gradient boosting framework with efficient linear model solver and tree learning algorithms. | 289 |
eric-ai-lab/fedvln | An open-source implementation of a federated learning framework to protect data privacy in embodied agent learning for Vision-and-Language Navigation. | 13 |
gbdt-pl/gbdt-pl | An implementation of a gradient boosting algorithm with piece-wise linear regression trees for efficient machine learning model training | 149 |
tqchen/xgboost | An optimized distributed gradient boosting library for machine learning | 571 |
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