A Systematic Review of Privacy-Aware Cloud Framework for Medical Secure E-Governance Data Processing

Qing Guan; Mustafa Muwafak Alobaedy; Mohd Nurul Hafiz Bin Ibrahim; S. B. Goyal

doi:10.57159/jcmm.5.1.25222

Authors

Qing Guan Faculty of Information Technology, City University Malaysia, Petaling Jaya, Selangor, Malaysia 46100; Gannan University of Science and Technology, Ganzhou, Jiangxi, China 341000
Mustafa Muwafak Alobaedy Faculty of Information Technology, City University Malaysia, Petaling Jaya, Selangor, Malaysia 46100; 4Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Selangor, Malaysia 63100
Mohd Nurul Hafiz Bin Ibrahim Faculty of Information Technology, City University Malaysia, Petaling Jaya, Selangor, Malaysia 46100
S. B. Goyal Chitkara University Institute of Engineering & Technology, Rajpura, Punjab, India 140401

DOI:

https://doi.org/10.57159/jcmm.5.1.25222

Keywords:

Systematic Review, E-Governance, Cloud Computing, Data Privacy, Encryption

Abstract

Cloud computing has greatly increased the effectiveness of e-governance, but there are also significant concerns about data security and privacy. The paper presents an in-depth evaluation of privacy-focused cloud architectures for the secure processing of medical e-governance data, in line with PRISMA. The study examined 72 peer-reviewed articles published after 2013 from IEEE Xplore, the ACM Digital Library, ScienceDirect, and SpringerLink. The study researched technologies, including AI-driven anomaly detection, hybrid cloud architecture, blockchain-enabled access management, and homomorphic encryption. This review organizes the available frameworks and evaluates how well they performed in previous studies. To build greater trust in digital governance systems, future trends point to lightweight encryption, cross-device functionality, and AI-powered security solutions. This in-depth examination of privacy-conscious frameworks identifies weaknesses in the research and offers helpful tips for both researchers and policymakers. The results indicate gaps in existing methodologies, thereby facilitating the development of e-governance infrastructures that are more secure, cost-efficient, and scalable, thereby enabling effective healthcare applications.

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