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PhantomFHE: A CUDA-Accelerated Fully Homomorphic Encryption Library

[!IMPORTANT]
This is a research project and is not intended for production use. We are actively working on improving the performance and usability of this library. If you have any questions or suggestions, please feel free to open an issue or contact us.

[!WARNING]
This project has been tested on Tesla A100 40G/80G, GTX 3080Ti/3090Ti/4090, AGX Xavier. Other GPUs may have compatibility issues and may not give correct results.

Documentation

Please read https://encryptorion-lab.gitbook.io/phantom-fhe/ for detailed instructions and explanations.

Features

License

This project (PhantomFHE) is released under GPLv3 license. See LICENSE for more information.

Some files contain the modified code from Microsoft SEAL. These codes are released under MIT License. See MIT License for more information.

Some files contain the modified code from OpenFHE. These codes are released under BSD 2-Clause License. See BSD 2-Clause License for more information.

Citation

If you use Phantom in your research, please cite the following paper:

Early access TDSC version (IEEE Xplore):

@article{10428046,
         author={Yang, Hao and Shen, Shiyu and Dai, Wangchen and Zhou, Lu and Liu, Zhe and Zhao, Yunlei},
         journal={IEEE Transactions on Dependable and Secure Computing}, 
         title={Phantom: A CUDA-Accelerated Word-Wise Homomorphic Encryption Library}, 
         year={2024},
         volume={},
         number={},
         pages={1-12},
         doi={10.1109/TDSC.2024.3363900}
}

IACR ePrint version (Cryptology ePrint Archive):

@misc{cryptoeprint:2023/049,
      author = {Hao Yang and Shiyu Shen and Wangchen Dai and Lu Zhou and Zhe Liu and Yunlei Zhao},
      title = {Phantom: A CUDA-Accelerated Word-Wise Homomorphic Encryption Library},
      howpublished = {Cryptology ePrint Archive, Paper 2023/049},
      year = {2023},
      doi = {10.1109/TDSC.2024.3363900},
      note = {\url{https://eprint.iacr.org/2023/049}},
      url = {https://eprint.iacr.org/2023/049}
}

If you are exploring BFV optimizations, please also cite the following paper:

@misc{cryptoeprint:2023/1429,
      author = {Shiyu Shen and Hao Yang and Wangchen Dai and Lu Zhou and Zhe Liu and Yunlei Zhao},
      title = {Leveraging GPU in Homomorphic Encryption: Framework Design and Analysis of BFV Variants},
      howpublished = {Cryptology ePrint Archive, Paper 2023/1429},
      year = {2023},
      note = {\url{https://eprint.iacr.org/2023/1429}},
      url = {https://eprint.iacr.org/2023/1429}
}

Roadmap

We are planning to support the following features in the future: