HeFUN: Homomorphic Encryption for Unconstrained Secure Neural Network Inference

HeFUN: Homomorphic Encryption for Unconstrained Secure Neural Network Inference

Homomorphic encryption (HE) has emerged as a pivotal technology for secure neural network inference (SNNI), offering privacy-preserving computations on encrypted data. Despite active developments in this field, HE-based SNNI frameworks are impeded by three inherent limitations. Firstly, they cannot...

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Bibliographic Details
Main Authors: Duy Tung Khanh Nguyen, Dung Hoang Duong, Willy Susilo, Yang-Wai Chow, The Anh Ta
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Future Internet
Subjects:
privacy-preserving machine learning
secure neural network inference
homomorphic encryption
Online Access:https://www.mdpi.com/1999-5903/15/12/407

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https://www.mdpi.com/1999-5903/15/12/407

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