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https://github.com/data61/python-paillier

A library for Partially Homomorphic Encryption in Python
https://github.com/data61/python-paillier

cryptography homomorphic-encryption paillier python

Last synced: 2 months ago
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A library for Partially Homomorphic Encryption in Python

Host: GitHub
URL: https://github.com/data61/python-paillier
Owner: data61
License: other
Created: 2014-11-05T07:15:28.000Z (over 9 years ago)
Default Branch: master
Last Pushed: 2023-08-04T08:19:39.000Z (11 months ago)
Last Synced: 2024-03-22T00:24:06.878Z (3 months ago)
Topics: cryptography, homomorphic-encryption, paillier, python
Language: Python
Size: 292 KB
Stars: 575
Watchers: 34
Forks: 130
Open Issues: 20
Metadata Files:
- Readme: README.rst
- Changelog: CHANGELOG.rst
- License: LICENSE.txt

Lists

awesome-he - python-paillier - Partially HE based on Paillier scheme. (Libraries)
awesome-fhe - python-paillier - Partially HE based on Paillier scheme. (Libraries / [Sunscreen](https://sunscreen.tech/))
awesome-stars - data61/python-paillier - A library for Partially Homomorphic Encryption in Python (Python)

README

        python-paillier  |release|

==========================

+---------------------+

|      |ciTest|       |

+---------------------+

|      |rtdM|         |

+---------------------+

|      |reqM|         |

+---------------------+

A Python 3 library implementing the Paillier Partially Homomorphic Encryption.

The homomorphic properties of the paillier crypto system are:

-  Encrypted numbers can be multiplied by a non encrypted scalar.

-  Encrypted numbers can be added together.

-  Encrypted numbers can be added to non encrypted scalars.

Citing

======

`python-paillier` is designed, developed and supported by `CSIRO's Data61 `__. If

you use any part of this library in your research, please cite it using the following BibTex entry::

    @misc{PythonPaillier,

      author = {CSIRO's Data61},

      title = {Python Paillier Library},

      year = {2013},

      publisher = {GitHub},

      journal = {GitHub Repository},

      howpublished = {\url{https://github.com/data61/python-paillier}},

    }

Running unit tests

------------------

::

   python setup.py test

Or use nose::

   nosetests

Note related to gmpy2

---------------------

`gmpy2` is not required to use the library, but is preferred. A pure Python implementation is available but 

`gmpy2` drastically improves performances. As indication on a laptop not dedicated to benchmarking, running the example

`examples/federated_learning_with_encryption.py` provided in the library took:

- 4.5s with `gmpy2` installed

- 35.7s without `gmpy2` installed

However, `gmpy2` is a requirement to run the tests.

Code History

------------

Developed at `Data61 | CSIRO `_.

Parts derived from the Apache licensed Google project:

https://code.google.com/p/encrypted-bigquery-client/

.. |release| image:: https://img.shields.io/pypi/v/phe.svg

    :target: https://pypi.python.org/pypi/phe/

    :alt: Latest released version on PyPi

.. |ciTest| image:: https://github.com/data61/python-paillier/actions/workflows/test.yml/badge.svg

    :target: https://github.com/data61/python-paillier/actions/workflows/test.yml

    :alt: CI Status

.. |reqM| image:: https://requires.io/github/data61/python-paillier/requirements.svg?branch=master

    :target: https://requires.io/github/data61/python-paillier/requirements/?branch=master

    :alt: Requirements Status of master

.. |rtdM| image:: https://readthedocs.org/projects/python-paillier/badge/?version=stable

   :target: http://python-paillier.readthedocs.org/en/latest/?badge=stable

   :alt: Documentation Status