concrete-ml
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| concrete-ml | magic-edit | |
|---|---|---|
| 8 | 1 | |
| 786 | 1,757 | |
| 6.1% | 0.4% | |
| 9.7 | 4.0 | |
| 3 days ago | 8 months ago | |
| Python | ||
| GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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concrete-ml
- Show HN: Logistic Regression Training on Encrypted Data with FHE
- Training ML Models on Encrypted Data with Homomorphic Encryption (FHE)
- FLaNK Stack Weekly 5 September 2023
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Concrete: A fully homomorphic encryption compiler
If you just want to dive right in, this example from Concrete ML's repository is very clear:
https://github.com/zama-ai/concrete-ml#a-simple-concrete-ml-...
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Instead of banning ChatGPT for its potential data theft, why don't we use advanced encryption techniques (for example, Homomorphic encryption) to secure our data?
As for ease of use, you should take a look at Concrete. It turns high level python code into FHE equivalents without developers having to know cryptography: https://github.com/zama-ai/concrete-ml
- Concrete ML: transform machine learning models into a homomorphic equivalent
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Zama Open-Sources Concrete ML v0.2 To Support Data Scientists Without Any Prior Cryptography Knowledge To Automatically Turn Classical Machine Learning (ML) Models Into Their FHE Equivalent
Github: https://github.com/zama-ai/concrete-ml
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[P] XGboost, sklearn and others running over encrypted data
Hello everyone! Following this post [numpy over encrypted numpy in fhe we are releasing a new lib that allows popular machine learning frameworks to run over encrypted data: https://github.com/zama-ai/concrete-ml
magic-edit
What are some alternatives?
concrete-numpy - Concrete-Numpy: A library to turn programs into their homomorphic equivalent.
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concrete - Concrete: TFHE Compiler that converts python programs into FHE equivalent
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