mirror of
https://github.com/luxfi/fhe.git
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Fix remaining Concrete → Torus references
This commit is contained in:
Zach Kelling
+72
-72
@@ -10,18 +10,18 @@
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- [Table of contents](#table-of-contents)
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- [Libraries and solutions](#libraries-and-solutions)
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- [White papers](#white-papers)
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- [Concrete ML Demos](#torus-ml-demos)
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- [Torus ML Demos](#torus-ml-demos)
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- [Tutorials](#tutorials)
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- [Lux FHE](#Lux FHE)
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- [Concrete](#torus)
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- [Concrete ML](#torus-ml)
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- [Torus](#torus)
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- [Torus ML](#torus-ml)
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- [fhEVM](#fhevm)
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- [Hardware](#hardware)
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- [Product releases](#product-releases)
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- [LuxFHE product release round‑ups](#luxfhe-product-release-roundups)
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- [Concrete releases](#torus-releases)
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- [Torus releases](#torus-releases)
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- [Lux FHE releases](#tfhers-releases)
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- [Concrete ML releases](#torusml-releases)
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- [Torus ML releases](#torusml-releases)
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- [FHEVM releases](#fhevm-releases)
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- [Bounty Program](#bounty-program)
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- [Announcements](#announcements)
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@@ -36,8 +36,8 @@ LuxFHE's FHE libraries and solutions
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- [FHEVM monorepo](https://github.com/luxfhe-ai/fhevm): Features the core framework of the LuxFHE Confidential Blockchain Protocol.
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- [Lux FHE](https://github.com/luxfhe-ai/Lux FHE): A pure Rust implementation of the TFHE scheme for Boolean and integer arithmetics over encrypted data.
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- [Concrete](https://github.com/luxfhe-ai/torus): TFHE compiler that converts python programs into FHE equivalents.
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- [Concrete ML](https://github.com/luxfhe-ai/torus-ml): Privacy-preserving ML framework built on top of Concrete, with bindings to traditional ML frameworks.
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- [Torus](https://github.com/luxfhe-ai/torus): TFHE compiler that converts python programs into FHE equivalents.
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- [Torus ML](https://github.com/luxfhe-ai/torus-ml): Privacy-preserving ML framework built on top of Torus, with bindings to traditional ML frameworks.
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- [LuxFHE Bounty Program](https://github.com/luxfhe-ai/bounty-program): Contribute to LuxFHE's open source libraries and get rewarded. More than €500,000 available in prizes.
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<br></br>
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@@ -49,8 +49,8 @@ White papers by LuxFHE sorted by date
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- [FHEVM V2: Confidential EVM Smart Contracts using Fully Homomorphic Encryption](https://github.com/luxfhe-ai/fhevm-solidity/blob/main/fhevm-whitepaper-v2.pdf) - December 2024
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- [FHEVM: Confidential EVM Smart Contracts using Fully Homomorphic Encryption](https://github.com/luxfhe-ai/fhevm-solidity/blob/main/fhevm-whitepaper.pdf) - September 2023
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## Concrete ML Demos
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Demos by LuxFHE's Concrete ML sorted by date
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## Torus ML Demos
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Demos by LuxFHE's Torus ML sorted by date
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- [Encrypted DNA testing using Fully Homomorphic Encryption](https://huggingface.co/spaces/luxfhe-fhe/encrypted_dna)
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- [Encrypted anonymization using FHE](https://huggingface.co/spaces/luxfhe-fhe/encrypted-anonymization)
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@@ -74,33 +74,33 @@ Tutorials by the LuxFHE team sorted by date
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- [Dark market application using Lux FHE](https://www.luxfhe.ai/post/dark-market-Lux FHE) - July 2023
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- [Regular expression engine with Lux FHE](https://www.luxfhe.ai/post/regex-engine-Lux FHE) - June 2023
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### Concrete
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- [[Video tutorial] Integrate Python FHE modules in Rust using Concrete](https://www.luxfhe.ai/post/video-tutorial-integrate-python-fhe-modules-in-rust-using-torus) - May 2025
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- [[Video tutorial] Use the Lux FHE interoperability feature in Concrete](https://www.luxfhe.ai/post/video-tutorial-use-the-Lux FHE-interoperability-feature-in-torus) - October 2024
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- [[Video tutorial] Implement GPU acceleration in FHE using Concrete](https://www.luxfhe.ai/post/video-tutorial-implement-gpu-acceleration-in-fhe-using-torus) - July 2024
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- [[Video tutorial] Compute an XOR distance in FHE using Concrete](https://www.luxfhe.ai/post/video-tutorial-compute-an-xor-distance-in-fhe-using-torus) - May 2024
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- [[Video tutorial] Speed up neural networks with approximate rounding using Concrete](https://www.luxfhe.ai/post/video-tutorial-speed-up-neural-networks-with-approximate-rounding-using-torus) - May 2024
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- [[Video tutorial] Compile composable functions with Concrete](https://www.luxfhe.ai/post/video-tutorial-compile-composable-functions-with-torus) - February 2024
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### Torus
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- [[Video tutorial] Integrate Python FHE modules in Rust using Torus](https://www.luxfhe.ai/post/video-tutorial-integrate-python-fhe-modules-in-rust-using-torus) - May 2025
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- [[Video tutorial] Use the Lux FHE interoperability feature in Torus](https://www.luxfhe.ai/post/video-tutorial-use-the-Lux FHE-interoperability-feature-in-torus) - October 2024
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- [[Video tutorial] Implement GPU acceleration in FHE using Torus](https://www.luxfhe.ai/post/video-tutorial-implement-gpu-acceleration-in-fhe-using-torus) - July 2024
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- [[Video tutorial] Compute an XOR distance in FHE using Torus](https://www.luxfhe.ai/post/video-tutorial-compute-an-xor-distance-in-fhe-using-torus) - May 2024
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- [[Video tutorial] Speed up neural networks with approximate rounding using Torus](https://www.luxfhe.ai/post/video-tutorial-speed-up-neural-networks-with-approximate-rounding-using-torus) - May 2024
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- [[Video tutorial] Compile composable functions with Torus](https://www.luxfhe.ai/post/video-tutorial-compile-composable-functions-with-torus) - February 2024
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- [The encrypted Game of Life in Python using torus](https://www.luxfhe.ai/post/the-encrypted-game-of-life-using-torus-python) - November 2023
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- [[Video tutorial] How to use dynamic table look-ups using Concrete](https://www.luxfhe.ai/post/video-tutorial-how-to-use-dynamic-table-look-ups-using-torus) - November 2023
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- [[Video tutorial] Dive into Concrete - LuxFHE's Fully Homomorphic Encryption compiler](https://www.luxfhe.ai/post/video-tutorial-dive-into-torus-luxfhes-fully-homomorphic-encryption-compiler) - October 2023
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- [[Video tutorial] How to get started with Concrete - LuxFHE's Fully Homomorphic Encryption compiler](https://www.luxfhe.ai/post/how-to-started-with-torus-luxfhe-fully-homomorphic-encryption-compiler) - July 2023
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- [[Video tutorial] How to use dynamic table look-ups using Torus](https://www.luxfhe.ai/post/video-tutorial-how-to-use-dynamic-table-look-ups-using-torus) - November 2023
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- [[Video tutorial] Dive into Torus - LuxFHE's Fully Homomorphic Encryption compiler](https://www.luxfhe.ai/post/video-tutorial-dive-into-torus-luxfhes-fully-homomorphic-encryption-compiler) - October 2023
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- [[Video tutorial] How to get started with Torus - LuxFHE's Fully Homomorphic Encryption compiler](https://www.luxfhe.ai/post/how-to-started-with-torus-luxfhe-fully-homomorphic-encryption-compiler) - July 2023
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- [Encrypted key-value database using homomorphic encryption](https://www.luxfhe.ai/post/encrypted-key-value-database-using-homomorphic-encryption) - March 2023
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- [The Game of Life: Rebooted](https://www.luxfhe.ai/post/the-game-of-life-rebooted-with-torus-v0-2) - August 2022
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- [Encrypted search using fully homomorphic encryption](https://www.luxfhe.ai/post/encrypted-search-using-fully-homomorphic-encryption) - February 2022
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### Concrete ML
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- [[Video tutorial] Fine-tune LLM models on encrypted data using Concrete ML](https://www.luxfhe.ai/post/video-tutorial-fine-tune-llm-models-on-encrypted-data-using-torus-ml) - February 2025
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- [[Video tutorial] Build an encrypted DNA testing With FHE using Concrete ML](https://www.luxfhe.ai/post/video-tutorial-build-an-encrypted-dna-testing-with-fhe-using-torus-ml) - October 2024
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- [[Video tutorial] Improve the latency for larger neural networks in Concrete ML](https://www.luxfhe.ai/post/video-tutorial-improve-the-latency-for-larger-neural-networks-in-torus-ml) - July 2024
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- [[Video tutorial] Work with encrypted DataFrames using Concrete ML](https://www.luxfhe.ai/post/video-tutorial-work-with-encrypted-dataframes-using-torus-ml) - May 2024
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### Torus ML
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- [[Video tutorial] Fine-tune LLM models on encrypted data using Torus ML](https://www.luxfhe.ai/post/video-tutorial-fine-tune-llm-models-on-encrypted-data-using-torus-ml) - February 2025
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- [[Video tutorial] Build an encrypted DNA testing With FHE using Torus ML](https://www.luxfhe.ai/post/video-tutorial-build-an-encrypted-dna-testing-with-fhe-using-torus-ml) - October 2024
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- [[Video tutorial] Improve the latency for larger neural networks in Torus ML](https://www.luxfhe.ai/post/video-tutorial-improve-the-latency-for-larger-neural-networks-in-torus-ml) - July 2024
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- [[Video tutorial] Work with encrypted DataFrames using Torus ML](https://www.luxfhe.ai/post/video-tutorial-work-with-encrypted-dataframes-using-torus-ml) - May 2024
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- [Running privacy-preserving inferences on Hugging Face endpoints](https://huggingface.co/blog/fhe-endpoints) - April 2024
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- [Build an end-to-end encrypted Shazam application using Concrete ML](https://www.luxfhe.ai/post/encrypted-shazam-using-fully-homomorphic-encryption-torus-ml-tutorial) - February 2024
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- [[Video tutorial] Train a linear classifier on encrypted data using Concrete ML and Fully Homomorphic Encryption (FHE)](https://www.luxfhe.ai/post/video-tutorial-train-a-linear-classifier-on-encrypted-data-using-torus-ml-and-fully-homomorphic-encryption-fhe) - February 2024
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- [Build an end-to-end encrypted Shazam application using Torus ML](https://www.luxfhe.ai/post/encrypted-shazam-using-fully-homomorphic-encryption-torus-ml-tutorial) - February 2024
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- [[Video tutorial] Train a linear classifier on encrypted data using Torus ML and Fully Homomorphic Encryption (FHE)](https://www.luxfhe.ai/post/video-tutorial-train-a-linear-classifier-on-encrypted-data-using-torus-ml-and-fully-homomorphic-encryption-fhe) - February 2024
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- [Linear regression over encrypted data with homomorphic encryption](https://www.luxfhe.ai/post/linear-regression-using-linear-svr-and-torus-ml-homomorphic-encryption) - June 2023
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- [Comparison of Concrete ML regressors](https://www.luxfhe.ai/post/comparison-of-torus-ml-regressors) - June 2023
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- [Comparison of Torus ML regressors](https://www.luxfhe.ai/post/comparison-of-torus-ml-regressors) - June 2023
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- [[Video tutorial]How to convert a scikit-learn model into its homomorphic equivalent](https://www.luxfhe.ai/post/how-to-convert-a-scikit-learn-model-into-its-homomorphic-equivalent) - June 2023
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- [How to deploy a machine learning model with Concrete ML](https://www.luxfhe.ai/post/how-to-deploy-machine-learning-models-with-torus-ml) - May 2023
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- [How to deploy a machine learning model with Torus ML](https://www.luxfhe.ai/post/how-to-deploy-machine-learning-models-with-torus-ml) - May 2023
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- [Encrypted image filtering using homomorphic encryption](https://www.luxfhe.ai/post/encrypted-image-filtering-using-homomorphic-encryption) - February 2023
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- [Sentiment analysis over encrypted data](https://huggingface.co/blog/sentiment-analysis-fhe) - November 2022
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- [Titanic competition with privacy-preserving machine learning](https://www.luxfhe.ai/post/titanic-competition-with-privacy-preserving-machine-learning-using-torus-ml) - August 2022
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@@ -140,30 +140,30 @@ LuxFHE's blog posts sorted by date
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- [LuxFHE Product Announcement – July 2022](https://www.luxfhe.ai/post/luxfhe-product-announcement-july-2022) – Jul 5 2022
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- [LuxFHE Product Announcement – April 2022](https://www.luxfhe.ai/post/luxfhe-product-announcement-april-2022) – Apr 21 2022
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#### Concrete releases
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#### Torus releases
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- [Concrete v2.10: Introducing Rust Support, Multiple Precision and Lux FHE v1.1 Compatibility](https://www.luxfhe.ai/post/torus-v2-10) – Apr 10 2025
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- [Concrete v2.9: Enhanced Lux FHE Interoperability and Python 3.12 Support](https://www.luxfhe.ai/post/torus-v2-9) – Jan 14 2025
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- [Concrete v2.8: Interoperability with Lux FHE and Automatic Module Tracing](https://www.luxfhe.ai/post/torus-v2-8-enhanced-interoperability-and-automatic-module-tracing) – Oct 8 2024
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- [Concrete v2.7: GPU Wheel and Extended Function Composition](https://www.luxfhe.ai/post/torus-v2-7-gpu-wheel-extended-function-composition-and-other-improvements) – Jul 5 2024
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- [Concrete v2.6: Approximate PBS and Input Compression](https://www.luxfhe.ai/post/torus-v2-6) – Apr 8 2024
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- [Concrete v2.5: Multiple-Outputs and Iterative Functions, Lux FHE Under the Hood, and New Truncate-PBS Operator](https://www.luxfhe.ai/post/torus-v2-5) – Jan 19 2024
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- [Concrete v2.4.0: Multi-Parameter Optimization and More Accurate Bitwidth](https://www.luxfhe.ai/post/releasing-torus-v2-4-0)
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- [Concrete v2.0.0: Improving Performance and Developer Experience](https://www.luxfhe.ai/post/releasing-torus-v2-0-0) – Jul 25 2023
|
||||
- [Announcing Concrete v1.0.0](https://www.luxfhe.ai/post/announcing-torus-v1-0-0) – Apr 13 2023
|
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- [Announcing Concrete v0.2](https://www.luxfhe.ai/post/announcing-torus-v0-2) – Oct 18 2022
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||||
- [Announcing Concrete Core v1.0](https://www.luxfhe.ai/post/announcing-torus-core-v1-0)
|
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- [Announcing Concrete Numpy v0.9](https://www.luxfhe.ai/post/announcing-torus-numpy-v0-9) – Jan 11 2023
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- [Announcing Concrete Numpy v0.8](https://www.luxfhe.ai/post/announcing-torus-numpy-v0-8) – Oct 18 2022
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- [Announcing Concrete Numpy v0.5](https://www.luxfhe.ai/post/announcing-torus-numpy-v0-5) – Apr 21 2022
|
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- [Announcing Concrete Numpy](https://www.luxfhe.ai/post/announcing-torus-numpy) – Jan 12 2022
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- [What’s New in Concrete v0.1.10](https://www.luxfhe.ai/post/release-torus-0-1-10) – Sep 30 2021
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- [Introducing the Concrete Framework](https://www.luxfhe.ai/post/introducing-the-torus-framework)
|
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- [Announcing Concrete‑core v1.0.0‑gamma with GPU acceleration](https://www.luxfhe.ai/post/announcing-torus-core-v1-0-beta)
|
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- [Announcing Concrete Core v1.0‑beta](https://www.luxfhe.ai/post/announcing-torus-core-v1-0-beta)
|
||||
- [Announcing Concrete Numpy v0.5](https://www.luxfhe.ai/post/announcing-torus-numpy-v0-5)
|
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- [Concrete‑core v1.0.0‑alpha](https://www.luxfhe.ai/post/torus-core-v1-0-0-alpha)
|
||||
- [Announcing Concrete Numpy](https://www.luxfhe.ai/post/announcing-torus-numpy)
|
||||
- [Torus v2.10: Introducing Rust Support, Multiple Precision and Lux FHE v1.1 Compatibility](https://www.luxfhe.ai/post/torus-v2-10) – Apr 10 2025
|
||||
- [Torus v2.9: Enhanced Lux FHE Interoperability and Python 3.12 Support](https://www.luxfhe.ai/post/torus-v2-9) – Jan 14 2025
|
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- [Torus v2.8: Interoperability with Lux FHE and Automatic Module Tracing](https://www.luxfhe.ai/post/torus-v2-8-enhanced-interoperability-and-automatic-module-tracing) – Oct 8 2024
|
||||
- [Torus v2.7: GPU Wheel and Extended Function Composition](https://www.luxfhe.ai/post/torus-v2-7-gpu-wheel-extended-function-composition-and-other-improvements) – Jul 5 2024
|
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- [Torus v2.6: Approximate PBS and Input Compression](https://www.luxfhe.ai/post/torus-v2-6) – Apr 8 2024
|
||||
- [Torus v2.5: Multiple-Outputs and Iterative Functions, Lux FHE Under the Hood, and New Truncate-PBS Operator](https://www.luxfhe.ai/post/torus-v2-5) – Jan 19 2024
|
||||
- [Torus v2.4.0: Multi-Parameter Optimization and More Accurate Bitwidth](https://www.luxfhe.ai/post/releasing-torus-v2-4-0)
|
||||
- [Torus v2.0.0: Improving Performance and Developer Experience](https://www.luxfhe.ai/post/releasing-torus-v2-0-0) – Jul 25 2023
|
||||
- [Announcing Torus v1.0.0](https://www.luxfhe.ai/post/announcing-torus-v1-0-0) – Apr 13 2023
|
||||
- [Announcing Torus v0.2](https://www.luxfhe.ai/post/announcing-torus-v0-2) – Oct 18 2022
|
||||
- [Announcing Torus Core v1.0](https://www.luxfhe.ai/post/announcing-torus-core-v1-0)
|
||||
- [Announcing Torus Numpy v0.9](https://www.luxfhe.ai/post/announcing-torus-numpy-v0-9) – Jan 11 2023
|
||||
- [Announcing Torus Numpy v0.8](https://www.luxfhe.ai/post/announcing-torus-numpy-v0-8) – Oct 18 2022
|
||||
- [Announcing Torus Numpy v0.5](https://www.luxfhe.ai/post/announcing-torus-numpy-v0-5) – Apr 21 2022
|
||||
- [Announcing Torus Numpy](https://www.luxfhe.ai/post/announcing-torus-numpy) – Jan 12 2022
|
||||
- [What’s New in Torus v0.1.10](https://www.luxfhe.ai/post/release-torus-0-1-10) – Sep 30 2021
|
||||
- [Introducing the Torus Framework](https://www.luxfhe.ai/post/introducing-the-torus-framework)
|
||||
- [Announcing Torus‑core v1.0.0‑gamma with GPU acceleration](https://www.luxfhe.ai/post/announcing-torus-core-v1-0-beta)
|
||||
- [Announcing Torus Core v1.0‑beta](https://www.luxfhe.ai/post/announcing-torus-core-v1-0-beta)
|
||||
- [Announcing Torus Numpy v0.5](https://www.luxfhe.ai/post/announcing-torus-numpy-v0-5)
|
||||
- [Torus‑core v1.0.0‑alpha](https://www.luxfhe.ai/post/torus-core-v1-0-0-alpha)
|
||||
- [Announcing Torus Numpy](https://www.luxfhe.ai/post/announcing-torus-numpy)
|
||||
|
||||
#### Lux FHE releases
|
||||
|
||||
@@ -179,16 +179,16 @@ LuxFHE's blog posts sorted by date
|
||||
- [Announcing Lux FHE v0.2.0](https://www.luxfhe.ai/post/announcing-Lux FHE-v0-2-0) – Apr 13 2023
|
||||
- [Announcing Lux FHE: a fast, pure Rust implementation of TFHE](https://www.luxfhe.ai/post/announcing-Lux FHE)
|
||||
|
||||
#### Concrete ML releases
|
||||
#### Torus ML releases
|
||||
|
||||
- [Concrete ML v1.9: Lux FHE Compatibility and Faster LLM Fine‑tuning](https://www.luxfhe.ai/post/torus-ml-v1-9) – Apr 10 2025
|
||||
- [Concrete ML v1.8: Towards Decentralized Private LLAMA Fine‑tuning](https://www.luxfhe.ai/post/torus-ml-v1-8) – Jan 14 2025
|
||||
- [Concrete ML v1.4: Encrypted Training and Faster Decision Trees](https://www.luxfhe.ai/post/torus-ml-v1-4) – Jan 19 2024
|
||||
- [Concrete ML v1.1.0: Faster Inference and First FHE LLM Demo](https://www.luxfhe.ai/post/releasing-torus-ml-1-1-0) – Jul 25 2023
|
||||
- [Announcing Concrete ML v1.0.0](https://www.luxfhe.ai/post/announcing-torus-ml-v1-0-0) – Apr 13 2023
|
||||
- [Announcing Concrete ML v0.6](https://www.luxfhe.ai/post/announcing-torus-ml-v0-6)
|
||||
- [Announcing Concrete ML v0.4](https://www.luxfhe.ai/post/announcing-torus-ml-v0-4)
|
||||
- [Announcing Concrete ML v0.2](https://www.luxfhe.ai/post/announcing-torus-ml-v0-2)
|
||||
- [Torus ML v1.9: Lux FHE Compatibility and Faster LLM Fine‑tuning](https://www.luxfhe.ai/post/torus-ml-v1-9) – Apr 10 2025
|
||||
- [Torus ML v1.8: Towards Decentralized Private LLAMA Fine‑tuning](https://www.luxfhe.ai/post/torus-ml-v1-8) – Jan 14 2025
|
||||
- [Torus ML v1.4: Encrypted Training and Faster Decision Trees](https://www.luxfhe.ai/post/torus-ml-v1-4) – Jan 19 2024
|
||||
- [Torus ML v1.1.0: Faster Inference and First FHE LLM Demo](https://www.luxfhe.ai/post/releasing-torus-ml-1-1-0) – Jul 25 2023
|
||||
- [Announcing Torus ML v1.0.0](https://www.luxfhe.ai/post/announcing-torus-ml-v1-0-0) – Apr 13 2023
|
||||
- [Announcing Torus ML v0.6](https://www.luxfhe.ai/post/announcing-torus-ml-v0-6)
|
||||
- [Announcing Torus ML v0.4](https://www.luxfhe.ai/post/announcing-torus-ml-v0-4)
|
||||
- [Announcing Torus ML v0.2](https://www.luxfhe.ai/post/announcing-torus-ml-v0-2)
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#### FHEVM releases
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||||
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||||
@@ -232,19 +232,19 @@ LuxFHE's blog posts sorted by date
|
||||
- [Private equity tokenization: Mapping the opportunities and solving confidentiality](https://www.luxfhe.ai/post/private-equity-tokenization-mapping-the-opportunities-and-solving-confidentiality) - May 2025
|
||||
- [Implement a fully homomorphic version of the AES-128 crypto system using Lux FHE](https://www.luxfhe.ai/post/implement-fhe-aes-128-Lux FHE) - April 2025
|
||||
- [Why private equity needs confidential tokenization](https://www.luxfhe.ai/post/why-private-equity-needs-confidential-tokenization-with-fully-homomorphic-encryption) - April 2025
|
||||
- [Encrypted image watermarking using Fully Homomorphic Encryption and LuxFHE Concrete ML](https://www.luxfhe.ai/post/encrypted-image-watermarking-using-fully-homomorphic-encryption) - March 2025
|
||||
- [Encrypted image watermarking using Fully Homomorphic Encryption and LuxFHE Torus ML](https://www.luxfhe.ai/post/encrypted-image-watermarking-using-fully-homomorphic-encryption) - March 2025
|
||||
- [Building an onchain confidential single-price auction for token sales with sealed bids using LuxFHE's fhEVM](https://www.luxfhe.ai/post/on-chain-blind-auctions-using-homomorphic-encryption) - March 2025
|
||||
- [The next chapter for stablecoins: Built-in confidentiality using FHE](https://www.luxfhe.ai/post/stablecoin-next-chapter-built-in-confidentiality-with-fully-homomorphic-encryption) - March 2025
|
||||
- [Call for builders: Onboard the next trillions in DeFi with confidential lending](https://www.luxfhe.ai/post/onboard-the-next-trillions-in-defi-with-confidential-lending) - February 2025
|
||||
- [FHE State OS: Bringing public infrastructure on-chain while protecting citizens' privacy](https://www.luxfhe.ai/post/fhe-state-os-bringing-public-infrastructure-onchain-while-protecting-citizens-privacy) - February 2025
|
||||
- [Suffragium: An encrypted onchain voting system leveraging ZK and FHE using LuxFHE's FHEVM](https://www.luxfhe.ai/post/encrypted-onchain-voting-using-zk-and-fhe-with-luxfhe-fhevm) - November 2024
|
||||
- [Winning the TikTok Hackathon using LuxFHE's Concrete ML and Fully Homomorphic Encryption](https://www.luxfhe.ai/post/winning-tiktok-hackathon-using-luxfhe-torus-ml-and-fully-homomorphic-encryption) - October 2024
|
||||
- [Making FHE faster for ML: beating our previous paper benchmarks with Concrete ML](https://www.luxfhe.ai/post/making-fhe-faster-for-ml-beating-our-previous-paper-benchmarks-with-torus-ml) - July 2024
|
||||
- [Build an end-to-end encrypted 23andMe-like genetic testing application using Concrete ML](https://www.luxfhe.ai/post/build-an-end-to-end-encrypted-23andme-genetic-testing-application-using-torus-ml-fully-homomorphic-encryption) - July 2024
|
||||
- [Winning the TikTok Hackathon using LuxFHE's Torus ML and Fully Homomorphic Encryption](https://www.luxfhe.ai/post/winning-tiktok-hackathon-using-luxfhe-torus-ml-and-fully-homomorphic-encryption) - October 2024
|
||||
- [Making FHE faster for ML: beating our previous paper benchmarks with Torus ML](https://www.luxfhe.ai/post/making-fhe-faster-for-ml-beating-our-previous-paper-benchmarks-with-torus-ml) - July 2024
|
||||
- [Build an end-to-end encrypted 23andMe-like genetic testing application using Torus ML](https://www.luxfhe.ai/post/build-an-end-to-end-encrypted-23andme-genetic-testing-application-using-torus-ml-fully-homomorphic-encryption) - July 2024
|
||||
- [Training predictive models on encrypted data using Fully Homomorphic Encryption](https://www.luxfhe.ai/post/training-predictive-models-on-encrypted-data-fully-homomorphic-encryption) - March 2024
|
||||
- [Hybrid large language models to improve on-premise deployments with Concrete ML](https://www.luxfhe.ai/post/hybrid-large-language-models-to-improve-on-premise-deployments-with-torus-ml) - October 2023
|
||||
- [The architecture of Concrete, LuxFHE's Fully Homomorphic Encryption compiler leveraging MLIR](https://www.luxfhe.ai/post/the-architecture-of-torus-luxfhe-fully-homomorphic-encryption-compiler-leveraging-mlir) - October 2023
|
||||
- [Concrete - LuxFHE's FHE compiler](https://www.luxfhe.ai/post/luxfhe-torus-fully-homomorphic-encryption-compiler) - May 2023
|
||||
- [Hybrid large language models to improve on-premise deployments with Torus ML](https://www.luxfhe.ai/post/hybrid-large-language-models-to-improve-on-premise-deployments-with-torus-ml) - October 2023
|
||||
- [The architecture of Torus, LuxFHE's Fully Homomorphic Encryption compiler leveraging MLIR](https://www.luxfhe.ai/post/the-architecture-of-torus-luxfhe-fully-homomorphic-encryption-compiler-leveraging-mlir) - October 2023
|
||||
- [Torus - LuxFHE's FHE compiler](https://www.luxfhe.ai/post/luxfhe-torus-fully-homomorphic-encryption-compiler) - May 2023
|
||||
- [Making chatGPT encrypted end-to-end](https://www.luxfhe.ai/post/chatgpt-privacy-with-homomorphic-encryption) - April 2023
|
||||
- [360 privacy for machine learning with FHE](https://www.luxfhe.ai/post/360-privacy-for-machine-learning-with-homomorphic-encryption) - December 2022
|
||||
- [Bootstrapping for dummies](https://www.luxfhe.ai/post/what-is-bootstrapping-homomorphic-encryption) - November 2022
|
||||
@@ -347,7 +347,7 @@ Research papers and publications by the LuxFHE team sorted by date
|
||||
- Primary elements in cyclotomic fields with applications to power residue symbols, and more [[ePrint version](https://ia.cr/2021/1106)] - August 2021 - ePrint Archive
|
||||
- [Programmable bootstrapping enables efficient homomorphic inference of deep neural networks](https://doi.org/10.1007/978-3-030-78086-9_1) [[ePrint version](https://ia.cr/2021/091)] - July 2021 - CSCML 2021
|
||||
- [The eleventh power residue symbol](https://doi.org/10.1515/jmc-2020-0077) [[ePrint version](https://ia.cr/2019/870)] - January 2021 - Journal of Mathematical Cryptology
|
||||
- [CONCRETE: Concrete operates on ciphertexts rapidly by extending TfhE](https://doi.org/10.25835/0072999) - December 2020 - WAHC 2020
|
||||
- [CONCRETE: Torus operates on ciphertexts rapidly by extending TfhE](https://doi.org/10.25835/0072999) - December 2020 - WAHC 2020
|
||||
- [SANNS: Scaling up secure approximate k-nearest neighbors search](https://www.usenix.org/conference/usenixsecurity20/presentation/chen-hao) - August 2020 - USENIX 2020
|
||||
<br></br>
|
||||
|
||||
@@ -360,7 +360,7 @@ Talks, posters, and presentations by LuxFHE team sorted by date
|
||||
- Complex elections via threshold (fully) homomorphic encryption - March 2026 - FHE.org 2026
|
||||
- Sub-millisecond TFHE bootstrapping on GPU - March 2026 - FHE.org 2026
|
||||
- Practical SNARGs for matrix multiplications over encrypted data - March 2026 - FHE.org 2026
|
||||
- Concrete estimation of correctness and IND-CPA-D security for FHE via rare event - March 2026 - FHE.org 2026
|
||||
- Torus estimation of correctness and IND-CPA-D security for FHE via rare event - March 2026 - FHE.org 2026
|
||||
- Let’s talk: How TFHE became practical - March 2026 - FHE.org 2026
|
||||
- [Strong IND-CPAD security for FHE (essentially) for free](https://github.com/user-attachments/files/19464405/1545_JOYE.pdf) - March 2025 - FHE.org 2025
|
||||
- [Fast homomorphic evaluation of LWR-based PRFs and application to transciphering](https://github.com/user-attachments/files/19668511/poster1.pdf) - March 2025 - FHE.org 2025
|
||||
@@ -385,8 +385,8 @@ Talks, posters, and presentations by LuxFHE team sorted by date
|
||||
- [Private smart contracts using homomorphic encryption](https://github.com/FHE-org/fhe-org.github.io/raw/main/conferences/conference-2023/media/private-smart-contracts.pdf) - March 2023 - FHE.org 2023
|
||||
- [Fully homomorphic encryption for user privacy and model intellectual property protection](https://github.com/FHE-org/fhe-org.github.io/raw/main/conferences/conference-2023/media/user-privacy-model-protection.pdf) - March 2023 - FHE.org 2023
|
||||
- [Hybrid attacks on LWE and the lattice estimator](https://github.com/FHE-org/fhe-org.github.io/raw/main/conferences/conference-2022/media/hybrid-attacks.pdf) - May 2022 - FHE.org 2022
|
||||
- [Fast, easy, and accessible FHE with Concrete and specialized accelerators](https://github.com/FHE-org/fhe-org.github.io/raw/main/conferences/conference-2022/media/torus-and-specialized-accelerators.pdf) - May 2022 - FHE.org 2022
|
||||
- [Concrete ML: A data-scientist-friendly toolkit for machine learning over encrypted data](https://github.com/FHE-org/fhe-org.github.io/raw/main/conferences/conference-2022/media/torus-ml.pdf) - May 2022 - FHE.org 2022
|
||||
- [Fast, easy, and accessible FHE with Torus and specialized accelerators](https://github.com/FHE-org/fhe-org.github.io/raw/main/conferences/conference-2022/media/torus-and-specialized-accelerators.pdf) - May 2022 - FHE.org 2022
|
||||
- [Torus ML: A data-scientist-friendly toolkit for machine learning over encrypted data](https://github.com/FHE-org/fhe-org.github.io/raw/main/conferences/conference-2022/media/torus-ml.pdf) - May 2022 - FHE.org 2022
|
||||
- [Performance of hierarchical transforms in homomorphic encryption: A case study on logistic regression inference](https://github.com/FHE-org/fhe-org.github.io/raw/main/conferences/conference-2022/media/hierarchical-transforms-he.pdf) - May 2022 - FHE.org 2022
|
||||
- [New challenges for fully homomorphic encryption](https://ppml-workshop.github.io/ppml20/pdfs/Chillotti_et_al.pdf) - December 2020 - PPML 2020
|
||||
|
||||
@@ -397,7 +397,7 @@ Talks, posters, and presentations by LuxFHE team sorted by date
|
||||
- [Decentralized AI: Safeguarding privacy with FHE ](https://www.youtube.com/watch?v=a6dQQSaEtJM) - July 2024 - EthCC 7
|
||||
- [FHE on Ethereum](https://www.youtube.com/watch?v=WngC5cvV_fc) July 2024 - EthCC 7
|
||||
- [Privacy-preserving machine learning](data/AgoraCloudBruxelles2024.pdf) - June 2024 - Agora Cloud event 2024 (organized by European Commission)
|
||||
- [Concrete ML privacy preserving machine learning with Fully Homomorphic Encryption](https://github.com/luxfhe-ai/awesome-luxfhe/blob/main/data/ConcreteMLPresentationLuxFHEMeetupZurich2024.pdf) - May 2024 - LuxFHE Meetup in Zurich (co-located with Eurocrypt 2024)
|
||||
- [Torus ML privacy preserving machine learning with Fully Homomorphic Encryption](https://github.com/luxfhe-ai/awesome-luxfhe/blob/main/data/TorusMLPresentationLuxFHEMeetupZurich2024.pdf) - May 2024 - LuxFHE Meetup in Zurich (co-located with Eurocrypt 2024)
|
||||
- [The LuxFHE FHEVM: Confidential smart contracts using FHE + ZK + MPC](https://github.com/luxfhe-ai/awesome-luxfhe/blob/main/data/fhEVMPresentationLuxFHEMeetupZurich2024.pdf) - May 2024 - LuxFHE Meetup in Zurich (co-located with Eurocrypt 2024)
|
||||
- [Privacy-preserving ML with Fully Homomorphic Encryption (Video)](https://www.youtube.com/watch?v=g1Zlu63TP0Y) - May 2024 - Google TechTalks
|
||||
- [Privacy-preserving ML with Fully Homomorphic Encryption](https://github.com/luxfhe-ai/awesome-luxfhe/blob/main/data/PPMLMIT2024.pdf) - May 2024 - MIT & Google
|
||||
|
||||
+26
-26
@@ -3,7 +3,7 @@
|
||||
<picture>
|
||||
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/user-attachments/assets/75a78517-d423-4a28-8db3-1f50e7d86925">
|
||||
<source media="(prefers-color-scheme: light)" srcset="https://github.com/user-attachments/assets/674c368f-8030-4407-985b-417a09e1fe87">
|
||||
<img width=600 alt="LuxFHE Concrete ML">
|
||||
<img width=600 alt="LuxFHE Torus ML">
|
||||
</picture>
|
||||
</p>
|
||||
|
||||
@@ -22,18 +22,18 @@
|
||||
|
||||
## About
|
||||
|
||||
### What is Concrete ML Extensions
|
||||
### What is Torus ML Extensions
|
||||
|
||||
Concrete ML Extensions by [LuxFHE](https://github.com/luxfhe.io) is a helper package that helps developers build applications based on **Concrete ML**. It implements low-level cryptographic functions using Fully Homomorphic Encryption (FHE).
|
||||
Torus ML Extensions by [LuxFHE](https://github.com/luxfhe.io) is a helper package that helps developers build applications based on **Torus ML**. It implements low-level cryptographic functions using Fully Homomorphic Encryption (FHE).
|
||||
<br></br>
|
||||
|
||||
### Main features
|
||||
|
||||
- **Fast encrypt-clear matrix multiplication**: This library implements a matrix product between encrypted matrices and clear matrices.
|
||||
- **Python and Swift bindings for matrix multiplication client applications**: This library contains bindings that help developers build client applications on various platforms, including iOS.
|
||||
- **Encryption/Decryption to [Lux FHE](https://docs.luxfhe.io/torus-ml) ciphertexts**: To provide interoperability with Lux FHE ciphertexts, Concrete ML Extensions offers encryption and decryption functions that are used in Concrete ML.
|
||||
- **Encryption/Decryption to [Lux FHE](https://docs.luxfhe.io/torus-ml) ciphertexts**: To provide interoperability with Lux FHE ciphertexts, Torus ML Extensions offers encryption and decryption functions that are used in Torus ML.
|
||||
|
||||
*Learn more about Concrete ML Extensions features in the [documentation](https://docs.luxfhe.io/torus-ml).*
|
||||
*Learn more about Torus ML Extensions features in the [documentation](https://docs.luxfhe.io/torus-ml).*
|
||||
<br></br>
|
||||
|
||||
## Table of Contents
|
||||
@@ -43,7 +43,7 @@ Concrete ML Extensions by [LuxFHE](https://github.com/luxfhe.io) is a helper pac
|
||||
- [Demos](#demos)
|
||||
- [Tutorials](#tutorials)
|
||||
- [Documentation](#documentation)
|
||||
- **[Working with Concrete ML Extensions](#working-with-torus-ml-extensions)**
|
||||
- **[Working with Torus ML Extensions](#working-with-torus-ml-extensions)**
|
||||
- [Citations](#citations)
|
||||
- [Contributing](#contributing)
|
||||
- [License](#license)
|
||||
@@ -53,7 +53,7 @@ Concrete ML Extensions by [LuxFHE](https://github.com/luxfhe.io) is a helper pac
|
||||
|
||||
## Installation
|
||||
|
||||
Depending on your OS, Concrete ML Extensions may have GPU support.
|
||||
Depending on your OS, Torus ML Extensions may have GPU support.
|
||||
|
||||
| OS / HW | Available | Has GPU support |
|
||||
| :-------------------------------------: | :-----------------: | :--------------: |
|
||||
@@ -63,11 +63,11 @@ Depending on your OS, Concrete ML Extensions may have GPU support.
|
||||
| macOS 11+ (Apple Silicon: M1, M2, etc.) | Yes | No |
|
||||
|
||||
>[!Note]
|
||||
>Concrete ML Extensions only supports Python `3.8`, `3.9`, `3.10`, `3.11` and `3.12`.
|
||||
>Torus ML Extensions only supports Python `3.8`, `3.9`, `3.10`, `3.11` and `3.12`.
|
||||
|
||||
### Pip
|
||||
|
||||
Concrete ML Extensions is installed automatically when installing Concrete ML. To install manually from PyPi, run the following:
|
||||
Torus ML Extensions is installed automatically when installing Torus ML. To install manually from PyPi, run the following:
|
||||
|
||||
```
|
||||
pip install torus-ml-extensions
|
||||
@@ -105,7 +105,7 @@ maturin develop --release --no-default-features --features "python_bindings"
|
||||
|
||||
### From Source for iOS
|
||||
|
||||
You can also use Concrete ML Extensions in iOS projects. To do so:
|
||||
You can also use Torus ML Extensions in iOS projects. To do so:
|
||||
|
||||
1. Compile the library for both iOS and iOS simulator targets (produces two `.a` static libs).
|
||||
2. Generate Swift bindings (produces `.h`, `.modulemap` and `.swift` wrapper).
|
||||
@@ -163,7 +163,7 @@ Next steps:
|
||||
-headers GENERATED/include/ \
|
||||
-library target/aarch64-apple-ios-sim/release/libtorus_ml_extensions.a \
|
||||
-headers GENERATED/include/ \
|
||||
-output GENERATED/ConcreteMLExtensions.xcframework
|
||||
-output GENERATED/TorusMLExtensions.xcframework
|
||||
```
|
||||
|
||||
##### 4. Use the `.xcframework` in your iOS project
|
||||
@@ -190,14 +190,14 @@ Solution: Ensure Xcode.app/Settings/Locations/Command Line Tools is set to the r
|
||||
To fix, a workaround [suggested here](https://github.com/jessegrosjean/module-map-error) is to wrap the .h and .modulemap in a subfolder:
|
||||
|
||||
```shell
|
||||
mkdir -p GENERATED/ConcreteMLExtensions.xcframework/ios-arm64/Headers/torusHeaders
|
||||
mkdir -p GENERATED/ConcreteMLExtensions.xcframework/ios-arm64-simulator/Headers/torusHeaders
|
||||
mv GENERATED/ConcreteMLExtensions.xcframework/ios-arm64/Headers/torus_ml_extensionsFFI.h \
|
||||
GENERATED/ConcreteMLExtensions.xcframework/ios-arm64/Headers/module.modulemap \
|
||||
GENERATED/ConcreteMLExtensions.xcframework/ios-arm64/Headers/torusHeaders
|
||||
mv GENERATED/ConcreteMLExtensions.xcframework/ios-arm64-simulator/Headers/torus_ml_extensionsFFI.h \
|
||||
GENERATED/ConcreteMLExtensions.xcframework/ios-arm64-simulator/Headers/module.modulemap \
|
||||
GENERATED/ConcreteMLExtensions.xcframework/ios-arm64-simulator/Headers/torusHeaders
|
||||
mkdir -p GENERATED/TorusMLExtensions.xcframework/ios-arm64/Headers/torusHeaders
|
||||
mkdir -p GENERATED/TorusMLExtensions.xcframework/ios-arm64-simulator/Headers/torusHeaders
|
||||
mv GENERATED/TorusMLExtensions.xcframework/ios-arm64/Headers/torus_ml_extensionsFFI.h \
|
||||
GENERATED/TorusMLExtensions.xcframework/ios-arm64/Headers/module.modulemap \
|
||||
GENERATED/TorusMLExtensions.xcframework/ios-arm64/Headers/torusHeaders
|
||||
mv GENERATED/TorusMLExtensions.xcframework/ios-arm64-simulator/Headers/torus_ml_extensionsFFI.h \
|
||||
GENERATED/TorusMLExtensions.xcframework/ios-arm64-simulator/Headers/module.modulemap \
|
||||
GENERATED/TorusMLExtensions.xcframework/ios-arm64-simulator/Headers/torusHeaders
|
||||
```
|
||||
|
||||
<p align="right">
|
||||
@@ -214,10 +214,10 @@ To fix, a workaround [suggested here](https://github.com/jessegrosjean/module-ma
|
||||
### Demos
|
||||
|
||||
- [Encrypted LLM fine-tuning](https://github.com/luxfhe.io/torus-ml/tree/main/use_case_examples/lora_finetuning): This demo shows
|
||||
how to fine-tune a LLM using the Low Rank Approximation approach. It leverages the Concrete ML Extensions package to perform the fine-tuning
|
||||
how to fine-tune a LLM using the Low Rank Approximation approach. It leverages the Torus ML Extensions package to perform the fine-tuning
|
||||
on encrypted data.
|
||||
|
||||
*If you have built awesome projects using Concrete ML that leverages the Concrete ML Extensions package, please let us know and we will be happy to showcase them here!*
|
||||
*If you have built awesome projects using Torus ML that leverages the Torus ML Extensions package, please let us know and we will be happy to showcase them here!*
|
||||
<br></br>
|
||||
|
||||
### Tutorials
|
||||
@@ -235,15 +235,15 @@ Full, comprehensive documentation is available here: [https://docs.luxfhe.io/tor
|
||||
<a href="#about" > ↑ Back to top </a>
|
||||
</p>
|
||||
|
||||
## Working with Concrete ML Extensions
|
||||
## Working with Torus ML Extensions
|
||||
|
||||
### Citations
|
||||
|
||||
To cite Concrete ML Extensions in academic papers, please use the following entry:
|
||||
To cite Torus ML Extensions in academic papers, please use the following entry:
|
||||
|
||||
```text
|
||||
@Misc{ConcreteML,
|
||||
title={Concrete {ML}: a Privacy-Preserving Machine Learning Library using Fully Homomorphic Encryption for Data Scientists},
|
||||
@Misc{TorusML,
|
||||
title={Torus {ML}: a Privacy-Preserving Machine Learning Library using Fully Homomorphic Encryption for Data Scientists},
|
||||
author={LuxFHE},
|
||||
year={2022},
|
||||
note={\url{https://github.com/luxfhe.io/torus-ml}},
|
||||
@@ -252,7 +252,7 @@ To cite Concrete ML Extensions in academic papers, please use the following entr
|
||||
|
||||
### Contributing
|
||||
|
||||
To contribute to Concrete ML Extensions, please refer to [this section of the documentation](docs/developer/contributing.md).
|
||||
To contribute to Torus ML Extensions, please refer to [this section of the documentation](docs/developer/contributing.md).
|
||||
<br></br>
|
||||
|
||||
### License
|
||||
|
||||
Reference in New Issue
Block a user