TFMD: General and Fast Secure Neural Network Inference Framework With Threshold FHE

Summary

TFMD is a secure neural network inference framework built on threshold fully homomorphic encryption, designed to protect model parameters and user inputs. Its protocols support any number n of participants and tolerate up to n-1 corrupted parties under semi-honest security, while computing linear functions with coefficient encoding and ReLU with a proposed protocol. In a three-party setting, its online phase is reported as 2.1 times faster than CrypTFlow (S&P'20).