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/