⚠️ This Library is now Deprecated

Liberate.FHE is no longer maintained.

It has been replaced by its successor, the DESILO FHE library.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 library@desilo.ai.

• View the new library here: https://fhe.desilo.dev/

Welcome to Liberate.FHE!

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.

Key Features

• RNS-CKKS scheme is supported.
• Python is natively supported.
• Multiple GPU acceleration is supported.
• Multiparty FHE is supported.

Quick Start

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.

How to Install with poetry

Clone this repository

git clone https://github.com/Desilo/liberate-fhe.git
cd liberate-fhe

Install dependencies

poetry install
poetry add setuptools

Run library build Script

poetry run python setup.py install

How to Install with pip

python setup.py install

Clone this repository

git clone https://github.com/Desilo/liberate-fhe.git
cd liberate-fhe

Install dependencies

pip install setuptools
pip install -e .

Run library build Script

python setup.py install

Documentation

Please refer to Liberate.FHE for detailed installation
instructions, examples, and documentation.

Citing Liberate.FHE

@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}},
}

License

• Liberate.FHE is available under the BSD 3-Clause Clear license. If you have any questions, please contact us at contact@desilo.ai.