Toy implementation of FHE algorithms
HEhub is a library for homomorphic encryption and its applications, and is part of the PrimiHub project.
HEonGPU is a high-performance library that optimizes Fully Homomorphic Encryption (FHE) on GPUs. Leveraging GPU parallelism, it reduces computational load through concurrent execution. Its multi-stream architecture minimizes data transfer overhead, making it ideal for large-scale encrypted computations with reduced latency.
Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning
A server-side CKKS GPU library fully interoperable with OpenFHE.
Single & Multi Key Homomorphic Encryption Library
SEAL.jl is an easy-to-use wrapper for the original SEAL library and supports homomorphic encryption with the BFV and CKKS schemes.
Fully Homomorphic Encryption for Private Federated Learning
Compiler-driven GPU acceleration of Fully Homomorphic Encryption
CKKS (Cheon-Kim-Kim-Song) scheme for calculation of a polynomial(3x^2+0.4x+1) using homomorphic encryption and Microsoft's SEAL library.
CKKS Bootstrapping using Microsoft SEAL
HIENAA (HE Implementation for Encrypted Numbers Arithmetic and Algorithms)
project for class CS05177
Source code for the paper "Lightweight Sorting in Approximate Homomorphic Encryption"
A Two-Party Secure Computation Protocol using Homomorphic Encryption
Logistic Regression model over encrypted data using Fully Homomorphic Encryption to detect credit card fraud, privately.
1. Machine Learning and Cyber Security Overview 2. Threats In AI Systems 3. Risk Mitigation and AI Deployment 4. AI for Cybersecurity
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