tf-encrypted
Encrypted machine learning framework
A framework for training and prediction on encrypted data using secure multi-party computation and homomorphic encryption in TensorFlow.
A Framework for Encrypted Machine Learning in TensorFlow
3 stars
1 watching
0 forks
last commit: over 4 years agoLinked from 2 awesome lists
jtoy/awesome-tensorflow
rdragos/awesome-mpcRelated projects:
| Repository | Description | Stars |
|---|---|---|
 tf-encrypted/tf-encrypted | Enables secure machine learning computations in TensorFlow without requiring expertise in cryptography or distributed systems. | 1,213 |
| tf-encrypted/moose | A secure distributed dataflow framework for encrypted machine learning and data processing | 59 |
 facebookresearch/crypten | A framework for applying secure computing techniques to machine learning models without modifying the underlying frameworks. | 1,554 |
 ai-secure/crfl | This project presents a framework for robust federated learning against backdoor attacks. | 71 |
 omarfoq/knn-per | A federated learning framework with personalized memorization using deep neural networks and k-nearest neighbors for collaborative learning of statistical models | 43 |
 microsoft/0xdeca10b | A framework for hosting and training machine learning models on a blockchain, enabling secure sharing and prediction without requiring users to pay for data or model updates. | 559 |
 adampetcher/fcf | A framework for machine-checked proofs of cryptography in the computational model. | 48 |
 zama-ai/concrete-ml | A framework for privacy-preserving machine learning using fully homomorphic encryption | 1,045 |
 jedld/tensor_stream | A Ruby-based framework for building and deploying machine learning models on various hardware platforms. | 506 |
 emstoudenmire/tnml | A software framework for using tensor networks to improve machine learning performance | 150 |
 tensorflow/tensorflow | An end-to-end platform for building and deploying machine learning applications | 186,822 |
| omarfoq/fedem | Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. | 157 |
 tmlr-group/fedfed | An approach to mitigating data heterogeneity in federated learning by sharing partial features of the data. | 17 |
 securefederatedai/openfl | A Python framework for collaborative machine learning without sharing sensitive data | 738 |
 b3nk4n/tensorlight | A high-level framework for machine intelligence applications using TensorFlow. | 11 |