Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on top of Concrete, with bindings to traditional ML frameworks.
A Fully Homomorphic Encryption (FHE) library for bridging the gap between theory and practice with a focus on performance and accuracy.
Zama Testnet App — Rich-styled CLI for Zama fully homomorphic encryption (FHE) testnet with confidential smart contract deployment, testnet ETH faucet claims, airdrop participation, Sepolia network integration, TFHE operations, and terminal interface for privacy-preserving blockchain development
Official mirror of Python-FHEz; Python Fully Homomorphic Encryption (FHE) Library for Encrypted Deep Learning as a Service (EDLaaS).
Flower framework for Federated Learning, with Fully Homomorphic Encryption integrated
Privacy-preserving LLM inference with CKKS homomorphic encryption and Private Linear Layer (PLL) protection for LoRA fine-tuned models
Experiments in using Z3 to check common FHE transformations
MPC key storage experiments for various FHE cryptosystems using Nillion's nilDB
Privacy-preserving disease risk prediction using the CKKS homomorphic encryption scheme.
Official Python SDK for H33 Post-Quantum Encryption Platform — Kyber + AES-256-GCM, FHE biometrics, zero-knowledge proofs
Official Python SDK for H33 Post-Quantum Authentication API — FHE + ZKP + Dilithium
Experiments in FHE and zkLLMs during Sage Bionetworks 2025 AI hackathon
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