Empowering SMPC: Bridging the Gap Between Scalability, Memory Efficiency and Privacy in Neural Network Inference

Jan 2024

Empowering SMPC: Bridging the Gap Between Scalability, Memory Efficiency and Privacy in Neural Network Inference

Authors: R. Burra, A. Tandon and S. Mittal

This paper aims to develop an efficient open-source Secure Multi-Party Computation (SMPC) repository, that addresses the issue of practical and scalable implementation of SMPC protocol on machines with moderate computational resources while aiming to reduce the execution time. We implement the ABY2.0 protocol for SMPC, providing developers with effective tools for building applications on the ABY 2.0 protocol. This article addresses the limitations of the C++ based MOTION2NX framework for secure neural network inference, including memory constraints and operation compatibility issues.

Journal/Conference

2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)