DeepGan-Privacy Preserving of HealthCare System Using DL

作     者：Sultan Mesfer Aldossary 

作者机构：Prince Sattam Bin Abdulaziz UniversityWadi Ad Dawaser11990Saudi Arabia 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第37卷第8期

页      面：2199-2212页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 0839[工学-网络空间安全] 08[工学] 0835[工学-软件工程] 081201[工学-计算机系统结构] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Healthcare cryptography deep learning adversarial network privacy 

摘      要：The challenge of encrypting sensitive information of a medical image in a healthcare system is still one that requires a high level of computing complexity,despite the ongoing development of *** looking through the previous research,it has become clear that the security issues still need to be looked into further because there is room for expansion in the research ***,neural networks have emerged as a cost-effective and effective optimization strategy in terms of providing security for *** revelation came about as a result of current ***,such an implementation is a technique that is expensive to compute and does not handle the huge variety of different assaults that may be made on *** primary objective of the system that has been described is to provide evidence of a complex framework in which deep neural networks have been applied to improve the efficiency of basic encryption *** research has led to the development and proposal of an enhanced version of methods that have previously been used to encrypt ***,the generative adversarial network(GAN),commonly known as GAN,will serve as the learning network that generates the private *** transformation domain,which reflects the one-of-a-kind fashion of the private key that is to be formed,is also meant to lead the learning network in the process of actually accomplishing the private key creation *** scheme may be utilized to train an excellent Deep Neural Networks(DNN)model while instantaneously maintaining the confidentiality of training medical *** was tested by the proposed approach DeepGAN on open-source medical datasets,and three sets of data:The Ultrasonic Brachial Plexus,the Montgomery County Chest X-ray,and the *** findings indicate that it is successful in maintaining both performance and privacy,and the findings of the assessment and the findings of the security investigation suggest that the de