BlockSecML: A Privacy-Preserving Machine Learning Framework Using Homomorphic Encryption, Advanced Encryption Standard-256 (AES-256), and Blockchain
BlockSecML is presented, a framework that brings together three technologies - Advanced Encryption Standard (AES)-256-Galois/Counter Mode encryption, Paillier partially homomorphic encryption (PHE), and Hyperledger Fabric blockchain - into a single working pipeline for privacy-preserving federated machine learning.