Abstract: This paper presents a hardware-accelerated polymorphic encryption framework for privacy-preserving machine learning. The approach employs a mode-switching polymorphic encryption scheme, ...

Abstract: Machine learning techniques with privacy protection capabilities (PPML) serve as essential security measures that protect data operations while maintaining model accuracy. The active pursuit ...