Privacy-Preserving Machine Learning With Fully Homomorphic Encryption for Deep Neural Network

Fully homomorphic encryption (FHE) is a prospective tool for privacy-preserving machine learning (PPML). Several PPML models have been proposed based on various FHE schemes and approaches. Although FHE schemes are suitable as tools for implementing PPML models, previous PPML models based on FHE, suc... View More