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Ensuring Security and Privacy in Cloud-Based Healthcare Information Systems Using Deep Learning Techniques
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Author(s): Shamneesh Sharma (upGrad Education Private Limited, India), Ajay Sharma (upGrad Education Private Limited, India)and Aman Kumar (upGrad Education Private Limited, India)
Copyright: 2024
Pages: 22
Source title:
Green AI-Powered Intelligent Systems for Disease Prognosis
Source Author(s)/Editor(s): Ashish Khanna (Maharaja Agrasen Institute of Technology, India)and Saikat Gochhait (Symbiosis Institute of Digital and Telecom Management, Symbiosis International (Deemed), India & Samara State Medical University, Russia)
DOI: 10.4018/979-8-3693-1243-8.ch015
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Abstract
The cloud-based system is a technology that is currently in the development phase and allows e-health information systems to store and exchange medical records. Nevertheless, it also exhibits significant privacy and security vulnerabilities. Deep learning techniques have recently shown great promise to protect the privacy and anonymity of these infrastructures. This chapter summarizes recent research in the field. This chapter discusses various security attacks, including malware and ransomware, phishing and social engineering, man-in-the-middle attacks, and denial-of-service attacks, as well as studies demonstrating the potential of deep learning techniques for detecting and preventing these attacks. These studies also demonstrate the potential of deep learning methods for safeguarding the confidentiality of sensitive health information. Despite the encouraging results of these studies, additional work is necessary to perfect deep-learning techniques for cloud-based e-health system security.
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