Enhancing Data Security in Cloud-Based Information Systems: A Systematic Literature Review
DOI:
https://doi.org/10.65080/mijai.v1.CM2601105003Keywords:
Cloud computing, data security, privacy protection, zero-trust architecture, AI-based security, homomorphic encryption, blockchain, federated identityAbstract
Objective: The rapid growth of cloud computing has changed how businesses handle, store, and access information. Nevertheless, this shift has raised complex security issues, particularly regarding security, integrity, and data availability. Traditional security strategies are inadequate because they cannot respond to the evolving threat landscape in an increasingly distributed, heterogeneous cloud infrastructure.
Aims: The proposed Systematic Literature Review (SLR) aims to synthesise existing knowledge on data security strategies in cloud-based information systems.
Methodology: Following the PRISMA approach, we searched peer-reviewed articles in the most prominent databases, namely IEEE, Scopus, SpringerLink, and ACM Digital Library, published between 2013 and 2024.
Results: The results indicated that data breaches, unauthorised access, insider threats, and multi-tenancy vulnerabilities are the most notable threats. The scientists propose different solutions to these risks, e.g., homomorphic encryption, zero-trust architectures, AI-based threat detection, blockchain auditing, and federated identity management. Despite these developments, scalability, legal compliance, real-time detection, and energy-efficient security measures are still missing.
Conclusion: This review highlights the need for hybrid, multi-layered defence models to ensure cloud resilience. It also calls for greater focus on privacy-preserving technologies and streamlining global policies. In general, the review highlights the adaptation, security, and sustainability of architectures that are essential to safeguard sensitive data within cloud ecosystems.
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Copyright (c) 2026 Yazeed Alsuhaibany (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.