Privacy-Preserving 3-Layer Neural Network Training

Fuente: arXiv
Saved in:
Bibliographic Details
Main Author: Chiang, John
Format: Preprint
Published: 2023
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866915242093576192
author Chiang, John
author_facet Chiang, John
contents In this manuscript, we consider the problem of privacy-preserving training of neural networks in the mere homomorphic encryption setting. We combine several exsiting techniques available, extend some of them, and finally enable the training of 3-layer neural networks for both the regression and classification problems using mere homomorphic encryption technique.
format Preprint
id arxiv_https___arxiv_org_abs_2308_09531
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Privacy-Preserving 3-Layer Neural Network Training
Chiang, John
Cryptography and Security
Machine Learning
In this manuscript, we consider the problem of privacy-preserving training of neural networks in the mere homomorphic encryption setting. We combine several exsiting techniques available, extend some of them, and finally enable the training of 3-layer neural networks for both the regression and classification problems using mere homomorphic encryption technique.
title Privacy-Preserving 3-Layer Neural Network Training
topic Cryptography and Security
Machine Learning
url https://arxiv.org/abs/2308.09531