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.
python-paillier
is designed, developed and supported by CSIRO's Data61 <https://www.data61.csiro.au/>
__. 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}},
}
::
python setup.py test
Or use nose::
nosetests
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.
Developed at Data61 | CSIRO <http://data61.csiro.au>
_.
Parts derived from the Apache licensed Google project: https://code.google.com/p/encrypted-bigquery-client/