Privacy-preserving convolutional neural network inference scheme based on homomorphic ciphertext transformation

To solve the problems of frequent interaction and low prediction accuracy of existing privacy-protected convolutional neural networks, a homomorphic friendly non-interactive privacy-protected convolutional neural network inference scheme was proposed via homomorphic ciphertext transformation. Utiliz...

詳細記述

書誌詳細

出版年:	Tongxin xuebao
主要な著者:	LI Ruiqi, YI Qin, HUANG Yixuan, JIA Chunfu
フォーマット:	論文
言語:	中国語
出版事項:	Editorial Department of Journal on Communications 2024-10-01
主題:	privacy-preserving convolutional neural network homomorphic encryption ciphertext transformation
オンライン･アクセス:	http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024216/