gradient-inversion-generative-image-prior
Gradient inversion vulnerability fix
An implementation of a method to invert gradients in federated learning to potentially reveal sensitive client data
39 stars
3 watching
6 forks
Language: Python
last commit: over 3 years ago Related projects:
Repository | Description | Stars |
---|---|---|
| This implementation allows an attacker to directly obtain user data from federated learning gradient updates by modifying the shared model architecture. | 23 |
| An implementation of an algorithm to recover input data from gradient information in neural networks. | 276 |
| This project presents an improved method to extract accurate private training data from publicly shared gradients in distributed learning systems. | 145 |
| An algorithm that breaks secure aggregation protocols in federated learning by recovering individual model updates from aggregated sums | 14 |
| A framework designed to protect federated learning models from hijacking attacks by identifying and removing compromised client gradients | 7 |
| This is a research project that extracts text from gradients with language model priors using deep learning techniques. | 23 |
| PyTorch implementation of a technique to improve the interpretability of deep learning models by adding noise to the gradients | 168 |
| A technique to simplify backpropagation in neural networks by selectively computing only the most relevant gradients | 110 |
| An implementation of gradient clipping as a method to mitigate the effects of noisy labels in machine learning models | 14 |
| An implementation of a deep learning-based image representation learning approach using a modified fully connected layer and transfer learning from VGG16 | 34 |
| An implementation of a gradient boosting algorithm with piece-wise linear regression trees for efficient machine learning model training | 151 |
| A tool to test the vulnerability of machine learning models to adversarial attacks | 562 |
| A Python library implementing a machine learning boosting framework with probabilistic prediction capabilities | 1,663 |
| Improves image restoration performance by converting global operations to local ones during inference | 231 |
| Recovery method for Federated Learning datasets using gradients to estimate instance-wise batch label restoration | 5 |