FILM
Language model attack
Recovering Private Text in Federated Learning of Language Models by attacking language models to extract private client data
Official repo for the paper: Recovering Private Text in Federated Learning of Language Models (in NeurIPS 2022)
57 stars
4 watching
7 forks
Language: Python
last commit: almost 2 years ago Related projects:
Repository | Description | Stars |
---|---|---|
| This project presents an attack on federated learning systems to compromise their privacy-preserving mechanisms. | 8 |
| A defense mechanism against model poisoning attacks in federated learning | 37 |
| This implementation allows an attacker to directly obtain user data from federated learning gradient updates by modifying the shared model architecture. | 23 |
| A tool for extracting machine learning models from cloud-based services using prediction APIs | 344 |
| A framework for attacking federated learning systems with adaptive backdoor attacks | 23 |
| 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 |
| A PyTorch framework for analyzing vulnerabilities in federated learning models and predicting data breaches | 274 |
| An adversarial attack framework on large vision-language models | 165 |
| An implementation of a defense against model inversion attacks in federated learning | 55 |
| Improves utility-privacy tradeoff in federated learning by reprogramming models to balance data utility and user privacy. | 5 |
| This repository provides an implementation of a differentially private federated learning algorithm designed to improve the robustness and performance of federated machine learning systems. | 42 |
| This repository provides an end-to-end language model capable of generating coherent text based on both spoken and written inputs. | 845 |
| A tool for demonstrating and analyzing attacks on federated learning systems by introducing backdoors into distributed machine learning models. | 179 |
| Simulates a federated learning setting to preserve individual data privacy | 365 |
| This repository provides an implementation of federated survival analysis using a deep learning framework. | 0 |