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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. 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.
Parts derived from the Apache licensed Google project: https://code.google.com/p/encrypted-bigquery-client/