tf-encrypted
privacy
| tf-encrypted | privacy | |
|---|---|---|
| 2 | 2 | |
| 1,203 | 1,919 | |
| 0.6% | 0.6% | |
| 0.0 | 7.8 | |
| 11 months ago | 12 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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tf-encrypted
- What are the technologies to keep the data secure when it's aggregated from multiple sources?
-
Facebook is reportedly trying to analyze encrypted data without deciphering it
There is a TF package for learning on encrypted data. Not familiar with the details or encryption algos supported.
https://github.com/tf-encrypted/tf-encrypted
privacy
What are some alternatives?
stanford-tensorflow-tutorials - This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
differential-privacy - Google's differential privacy libraries.
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. [Moved to: https://github.com/horovod/horovod]
Differential-Privacy-Guide - Differential Privacy Guide
dp-xgboost
openfl - The Open Flash Library for creative expression on the web, desktop, mobile and consoles.
EnvisEdge - Deploy recommendation engines with Edge Computing
openfl - An open framework for Federated Learning.
tf2-published-models - Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard.
mia - A library for running membership inference attacks against ML models
adversarial-robustness-toolbox - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams