concrete-ml
FHE ML framework
A framework for privacy-preserving machine learning using fully homomorphic encryption
Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on top of Concrete, with bindings to traditional ML frameworks.
1k stars
21 watching
148 forks
Language: Python
last commit: about 1 month ago
Linked from 2 awesome lists
data-sciencefhefully-homomorphic-encryptionhomomorphic-encryptionmachine-learningppmlprivacypythonscikit-learntfhetorch
Related projects:
Repository | Description | Stars |
---|---|---|
zama-ai/concrete | A compiler that converts Python programs into homomorphic encryption algorithms | 1,270 |
zama-ai/tfhe-rs | An implementation of homomorphic encryption schemes for secure numerical computations over encrypted data | 980 |
zama-ai/fhevm | A Solidity library that enables developers to write confidential smart contracts on the EVM using fully homomorphic encryption. | 436 |
facebookresearch/crypten | A framework for applying secure computing techniques to machine learning models without modifying the underlying frameworks. | 1,554 |
trustworthycomputing/t2-fhe-compiler-and-benchmarks | A framework providing a standardized benchmark suite and cross compiler for fully homomorphic encryption libraries | 34 |
ai-secure/crfl | This project presents a framework for robust federated learning against backdoor attacks. | 71 |
tf-encrypted/tf-encrypted | Enables secure machine learning computations in TensorFlow without requiring expertise in cryptography or distributed systems. | 1,213 |
vernamlab/cufhe | A CUDA-accelerated Fully Homomorphic Encryption Library | 213 |
openfheorg/openfhe-development | A library for implementing fully homomorphic encryption | 780 |
h2oai/article-information-2019 | A framework for building and evaluating machine learning systems with high accuracy and interpretability, particularly in human-centered applications. | 13 |
kryptnostic/krypto | An implementation of multivariate quadratic fully homomorphic encryption in C++ | 50 |
latticex-foundation/rosetta | Provides privacy-preserving solutions for artificial intelligence without requiring expertise in cryptography or trusted execution environments. | 566 |
lducas/fhew | A library that enables secure computation on encrypted data using a symmetric encryption scheme and arbitrary boolean circuits. | 222 |
vernamlab/cuhe | A CUDA-accelerated library for homomorphic encryption and evaluation of polynomial rings. | 195 |
mortendahl/tf-encrypted | A framework for training and prediction on encrypted data using secure multi-party computation and homomorphic encryption in TensorFlow. | 3 |