concrete
concrete-ml
concrete | concrete-ml | |
---|---|---|
5 | 8 | |
1,121 | 786 | |
2.8% | 6.1% | |
9.7 | 9.7 | |
2 days ago | 2 days ago | |
C++ | Python | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
concrete
- Concrete: Converts Python programs into homomorphic encryption equivalent
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Is there a Rust equivalent for Fully Homomorphic Encryption?
There is concrete for homomorphic encryption, but that is not really a transport/compiler (yet).
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Official /r/rust "Who's Hiring" thread for job-seekers and job-offerers [Rust 1.59]
Your team is writing and maintaining a cryptographic library in Rust. You will contribute in making it fast and easy to use. This library is indeed intended for growing with new cryptographic algorithms, new hardware implementations, etc.
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cryptography.rs: showcase of notable cryptography libraries developed in Rust (a.k.a. Awesome Rust Cryptography)
We are building Concrete, a fast Rust library for homomorphic encryption. https://github.com/zama-ai/concrete
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Facebook Joins the Rust Foundation
Awesome. I've been keeping an eye on Zama AI, and in particular their Concrete[0] library. Glad to see they're a member now.
[0] https://github.com/zama-ai/concrete/
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
What are some alternatives?
foundation.rust-lang.org - website for Rust Foundation
concrete-numpy - Concrete-Numpy: A library to turn programs into their homomorphic equivalent.
zmsg - A zero knowledge messaging system built on zcash.
yolov7-object-tracking - YOLOv7 Object Tracking Using PyTorch, OpenCV and Sort Tracking
phpass - PHPass, the WordPress password hasher, re-implemented in rust
puck - The visual editor for React
libreddit - Private front-end for Reddit
openaidemo - Demo of how access the OpenAI API using Java 17
RCIG_Coordination_Repo - A Coordination repo for all things Rust Cryptography oriented
privaxy - Privaxy is the next generation tracker and advertisement blocker. It blocks ads and trackers by MITMing HTTP(s) traffic.
ire - I2P router implementation in Rust
paxml - Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.