This repository contains the implementation code for "slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference" that is accepted at 5th Workshop on Cloud Security and Privacy (Cloud S&P 2023). As the title suggests, "slytHErin" provides modular blocks to easily build neural network which can be used for privacy-preserving inference under. homomorphic encryption under different scenarios and threat model
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This folder contains python scripts for training the models used for evaluation in the paper.
It contains serialization scripts for porting these models into a format which can be used by the inference part of the framework.
For more details refer to /training/README.md
This folder contains the main framework written in Go for privacy-preserving inference using homomorphic encryption.
For more details refer to /inference/README.md