Securing the cloud: Advanced solutions for government data protection
1 Cornell University, SC Johnson Business School, Ithaca, NY, USA.
2 Indiana University, Kelley School of Business, Bloomington, IN, USA.
Review Article
World Journal of Advanced Research and Reviews, 2024, 23(02), 901–905
Publication history:
Received on 30 June 2024; revised on 08 August 2024; accepted on 10 August 2024
Abstract:
This study examines government agencies' critical security challenges when adopting cloud-based solutions. As governments increasingly migrate their services to the cloud to enhance efficiency and reduce costs, they must contend with significant risks, including data breaches, unauthorized access, and regulatory compliance. To mitigate these threats, the paper explores implementing robust security measures such as advanced encryption methods, multi-factor authentication (MFA), continuous monitoring, and Zero Trust Architecture. The research emphasizes the importance of adhering to international security standards like ISO 27001 and NIST guidelines to ensure data integrity and protect sensitive government information. Additionally, the study highlights the role of AI and machine learning (ML) technologies in enhancing security measures and automating threat detection. By leveraging these advanced security protocols, government agencies can safeguard digital assets while improving service delivery and public trust. The findings of this research suggest that a well-secured cloud infrastructure is essential for the modernization of government services, significantly enhancing operational efficiency, regulatory compliance, and citizen engagement. These insights underscore the necessity of continuous investment in cloud security to support the evolving needs of digital governance.
Keywords:
Cloud Security; Government Data Protection; AI in Cloud Security; ISO 27001; NIST Guidelines; Machine Learning (ML) for Security
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0