concrete-numpy
python-fhez
| concrete-numpy | python-fhez | |
|---|---|---|
| 4 | 2 | |
| 226 | - | |
| - | - | |
| 4.7 | - | |
| 13 days ago | - | |
| Python | ||
| GNU General Public License v3.0 or later | - |
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concrete-numpy
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[P] ML over Encrypted Data
Hi everyone, we have developed a library that applies numpy functions over encrypted data (using homomorphic encryption). The repo is available in open source at https://github.com/zama-ai/concrete-numpy
- Compile NumPy Functions to Their Fully Homomorphic Encryption (FHE) Equivalents
- Concrete Numpy: compile various Numpy functions into their Fully Homomorphic Encryption (#FHE) equivalents.
- Concrete-Numpy: Data Science and Machine Learning over encrypted data.
python-fhez
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[P] Python-FHEz Fully Homomorphically Encrypted Deep Learning Library
- You can find Python-FHEz here: https://gitlab.com/deepcypher/python-fhez
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[P] ML over Encrypted Data
Hey now I can't say anything about concrete, but from my experience with MS-SEAL it is an order of magnitude slower on cyphertexts than the straight addition or multiplication on the plaintext message. You can try it out using one of my own libraries in a jupyter notebook here: https://gitlab.com/deepcypher/python-fhez/ in the examples directory, on Fashion-MNIST (for how see: https://python-fhez.readthedocs.io/en/latest/examples.html) . I am working on a sister project using go and lattigo to see if I can improve performance as the real problem is not only is FHE slower but wrapping it in a language like python with numpy custom containers (which is also what concrete does AFAIK) adds probably even more time and lots of space too!
What are some alternatives?
concrete-ml - Concrete ML: Privacy Preserving ML framework built on top of Concrete, with bindings to traditional ML frameworks.
mlcourse.ai - Open Machine Learning Course
sspipe - Simple Smart Pipe: python productivity-tool for rapid data manipulation
liberate-fhe - A Fully Homomorphic Encryption (FHE) library for bridging the gap between theory and practice with a focus on performance and accuracy.
heflow - Open source platform for the privacy-preserving machine learning lifecycle
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis