Homomorphic Encryption processing Unit (HEU) is a subproject of Secretflow that implements high-performance homomorphic encryption algorithms.
Project description
HEU
HEU (Homomorphic Encryption processing Unit) is a user-friendly and high-performance homomorphic encryption library that supports multiple types and scalable hardware acceleration.
document
https://www.secretflow.org.cn/docs/heu/
Repo status
Homomorphic encryption algorithms are mainly divided into two categories: partially homomorphic encryption (PHE) and fully homomorphic encryption (FHE). Currently, HEU supports most PHE algorithms, while FHE is still under development and will take some time.
Supported algorithms:
- Additive homomorphic encryption
- Paillier (recommended)
- Okamoto–Uchiyama (recommended)
- EC ElGamal
- Damgard-Jurik
- Damgard-Geisler-Krøigaard (DGK)
- Fully homomorphic encryption
- Under development and is the current focus of work.
Each algorithm includes a variety of different implementations, and some implementations support hardware accelerators. For more details, please refer to the Document
Layout
.
├── .circleci # CI/CD configuration files for circleci
├── .github # Configuration files for GitHub
├── docs # HEU documentation in Sphinx format
├── heu # All the implementation code for HEU
│ ├── algorithms # Holds the implementations of all algorithms
│ ├── experimental # Contains some standalone experimental code
│ ├── library # Implements the application layer functionality of the HE Library
│ │ ├── algorithms # Legacy algorithms not yet migrated to SPI (this directory will be deprecated after migration)
│ │ ├── benchmark # Contains benchmarking code
│ │ ├── numpy # Implements a set of Numpy-like interfaces
│ │ └── phe # PHE Dispatcher implementation (to be deprecated, with replaced by SPI)
│ ├── pylib # Python bindings
│ └── spi # Defines the HEU software and hardware access layer interface (SPI)
│ ├── he # Contains HE SPI and related Sketches
│ └── poly # Defines polynomial interfaces and related Sketches
└── third_party # Contains third-party libraries required for compilation; libraries will be automatically downloaded during build
HEU is currently transitioning from the old Dispatcher architecture to an SPI-based framework. The main modules and their code path mappings for both architectures are as follows:
Dispatcher-based architecture:
Python APIs (Python binding)
PATH: heu/pylib
│
├───────────────────┐
│ ▼
│ Tensor Lib with Numpy-like API
│ PATH: heu/library/numpy
│ │
│ ┌─────────────┘
│ │
▼ ▼
PHE Dispatcher & PHE C++ API
PATH: heu/library/phe
│
│
▼
Various PHE algorithm implementations
PATH: heu/library/algorithms
SPI-based architecture:
Python APIs (Python binding)
PATH: heu/pylib
│
├───────────────────┐
│ ▼
│ Tensor Lib with Numpy-like API
│ PATH: heu/numpy
│ │
│ ┌─────────────────┘
│ │
▼ ▼
HE SPI (C++ APIs)
PATH: heu/spi/he
│
│
▼
Various HE algorithm implementations
PATH: heu/algorithms
For a more detailed introduction to SPI, please click here
2024 Work Plan
Architecture Transition Milestones:
- HE SPI: Designed a unified interface that supports all PHE/FHE algorithms.
- Implementation of SPI Sketches. (in progress)
- Migration of existing algorithms to SPI. (in progress)
- Automated testing framework for PHE/FHE algorithms. (in progress)
- Transition of Tensor Lib's underlying layer from Dispatcher to SPI.
- Transition of PyLib's underlying layer from Dispatcher to SPI.
FHE Milestones:
- Integration of Microsoft SEAL
- Integration of OpenFHE.
- Support for GPU-accelerated CKKS algorithm.
- Provides FHE interfaces in Tensor Lib.
- Provides FHE interfaces in PyLib.
Compile and install
Environmental requirements
- CPU
- x86_64: minimum required AVX instruction set
- AArch64: ARMv8
- OS
- Ubuntu 18.04+
- Centos 7
- macOS 12.0+ (macOS Monterey+)1
- Python
- Python 3.9+
- Due to CI resource limitation, macOS x64 prebuild binary is no longer available.
Install via Pip
pip install sf-heu
Install from source
The following command will automatically compile and install HEU into the default Python environment:
git clone git@github.com:secretflow/heu.git
cd heu
sh build_wheel_entrypoint.sh
Run unit tests (optional)
# just compile, do not run any UT (optional)
bazel build heu/...
# compile and run all UTs
bazel test heu/...
Contribution Guidelines
SecretFlow is an open and inclusive community, and we welcome any kind of contribution. If you want to improve HEU, please refer to Contribution Guide
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distributions
File details
Details for the file sf_heu-0.6.0.dev20241015-cp310-cp310-manylinux_2_28_aarch64.whl
.
File metadata
- Download URL: sf_heu-0.6.0.dev20241015-cp310-cp310-manylinux_2_28_aarch64.whl
- Upload date:
- Size: 6.1 MB
- Tags: CPython 3.10, manylinux: glibc 2.28+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.10.15
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6a6e618d95a0c6f956f14379379f5007ceea1cd221656d30a8256b110b0f1fad |
|
MD5 | 14159c714fed3a7117caa7e42829610e |
|
BLAKE2b-256 | 89ddd569c019e3de3545fe051600dfc252fd9510fda2597911cc53235df1ea56 |
File details
Details for the file sf_heu-0.6.0.dev20241015-cp310-cp310-manylinux2014_x86_64.whl
.
File metadata
- Download URL: sf_heu-0.6.0.dev20241015-cp310-cp310-manylinux2014_x86_64.whl
- Upload date:
- Size: 6.3 MB
- Tags: CPython 3.10
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.10.15
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6b159af3156ae45948c7757c1aa68a30979970ac645f0408f0734de2a7e4aee6 |
|
MD5 | 9bafd09633724efb9e989c7b6c00c4d3 |
|
BLAKE2b-256 | ebd2dd2432d435ebeb853d9eff2a6914d127de6753d71b58aa0b8ab3002242f2 |
File details
Details for the file sf_heu-0.6.0.dev20241015-cp310-cp310-macosx_11_0_arm64.whl
.
File metadata
- Download URL: sf_heu-0.6.0.dev20241015-cp310-cp310-macosx_11_0_arm64.whl
- Upload date:
- Size: 4.1 MB
- Tags: CPython 3.10, macOS 11.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.10.15
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5f61668ed2ed6ccbdf4b9e664b662566a2f5733fdc4036e50a53a491044e8da9 |
|
MD5 | 77b40cba6760bd2cfdd7ee9a9c67c2ba |
|
BLAKE2b-256 | 6782d3f50bcc0c0e37489464e62c8b76cf01173b564c8249f0c22fd206a1f88f |