Privacy Set: Privacy-Authority-Aware Compiler for Homomorphic Encryption on Edge-Cloud System

Fully homomorphic encryption (FHE) offers a promising solution for privacy-preserving cloud computing by allowing cloud servers to compute on encrypted data without decryption. However, its applicability is limited by the programming burden of ciphertext management and considerable operational latency. Recently proposed FHE compilers automate ciphertext management, but they transform all data into ciphertexts without filtering private data, thus unnecessarily increasing FHE ciphertexts and the overall latency. This work introduces a new privacy-authority type, called privacy-set (PSet), that allows programmers to annotate authorized devices for each unit of private data. Moreover, this work proposes a new privacy authority-aware compiler that automatically transforms a PSet-annotated plain program into an FHE-enabled edge-cloud cooperative program with operation authority- and latency-aware partitioning. This work evaluates the PSet compiler with six machine learning and deep learning applications, and demonstrates that the PSet compiler performs 4.92 times faster than the existing FHE compilers that do not support edge-cloud partitioning.