Enhancing Data Privacy Protection and Feature Extraction in Secure Computing Using a Hash Tree and Skip Attention Mechanism

Enhancing Data Privacy Protection and Feature Extraction in Secure Computing Using a Hash Tree and Skip Attention Mechanism

This paper addresses the critical challenge of secure computing in the context of deep learning, focusing on the pressing need for effective data privacy protection during transmission and storage, particularly in sensitive fields such as finance and healthcare. To tackle this issue, we propose a no...

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Bibliographic Details
Main Authors: Zizhe Zhou, Yaqi Wang, Lin Cong, Yujing Song, Tianyue Li, Meishu Li, Keyi Xu, Chunli Lv
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Applied Sciences
Subjects:
data privacy protection
deep learning
encryption visualization
skip loss function
Online Access:https://www.mdpi.com/2076-3417/14/22/10687
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