Liberate.FHE is no longer maintained.
It has been replaced by its successor, the DESILO FHE library. We highly recommend using this new library, which is easier to use and has more functionalities, including bootstrap. If you have any questions, please contact us at [email protected].
- View the new library here: https://fhe.desilo.dev/
Liberate.FHE is an open-source Fully Homomorphic Encryption (FHE) library for bridging the gap between theory and practice with a focus on performance and accuracy.
Liberate.FHE is designed to be user-friendly while delivering robust performance, high accuracy, and a comprehensive suite of convenient APIs for developing real-world privacy-preserving applications.
Liberate.FHE is a pure Python and CUDA implementation of FHE. So, Liberate.FHE supports multi-GPU operations natively.
The main idea behind the design decisions is that non-cryptographers can use the library; it should be easily hackable and integrated with more extensive software frameworks.
Additionally, several design decisions were made to maximize the usability of the developed software:
- Make the number of dependencies minimal.
- Make the software easily hackable.
- Set the usage of multiple GPUs as the default.
- Make the resulting library easily integrated with the pre-existing software, especially Artificial Intelligence (AI) related ones.
- RNS-CKKS scheme is supported.
- Python is natively supported.
- Multiple GPU acceleration is supported.
- Multiparty FHE is supported.
from liberate import fhe
from liberate.fhe import presets
# Generate CKKS engine with preset parameters
grade = "silver" # logN=15
params = presets.params[grade]
engine = fhe.ckks_engine(**params, verbose=True)
# Generate Keys
sk = engine.create_secret_key()
pk = engine.create_public_key(sk)
evk = engine.create_evk(sk)
# Generate test data
m0 = engine.example(-1, 1)
m1 = engine.example(-10, 10)
# encode & encrypt data
ct0 = engine.encorypt(m0, pk)
ct1 = engine.encorypt(m1, pk, level=5)
# (a + b) * b - a
result = (m0 + m1) * m1 - m0
ct_add = engine.add(ct0, ct1) # auto leveling
ct_mult = engine.mult(ct1, ct_add, evk)
ct_result = engine.sub(ct_mult, ct0)
# decrypt & decode data
result_decrypted = engine.decrode(ct_result, sk)If you would like a detailed explanation, please refer to the official documentation.
git clone https://github.com/Desilo/liberate-fhe.git
cd liberate-fhepoetry install
poetry add setuptoolspoetry run python setup.py installpython setup.py install
git clone https://github.com/Desilo/liberate-fhe.git
cd liberate-fhepip install setuptools
pip install -e .python setup.py installPlease refer to Liberate.FHE for detailed installation instructions, examples, and documentation.
@Misc{Liberate_FHE,
title={{Liberate.FHE: A New FHE Library for Bridging the Gap between Theory and Practice with a Focus on Performance and Accuracy}},
author={DESILO},
year={2023},
note={\url{https://github.com/Desilo/liberate-fhe}},
}
- Liberate.FHE is available under the BSD 3-Clause Clear license. If you have any questions, please contact us at [email protected].