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ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

Peer Reviewed and Referred Journal || Free Certificate of Publication

Research and review articles are invited for publication in March 2026 (Volume 18, Issue 3) Submit manuscript

Framework for Cloud Data Security Using Agentic AI

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  • Framework for Cloud Data Security Using Agentic AI

Naseer R, Srujan K M *, Deepthi A S, Divyashree C H and Goutham M

Department of Computer Science & Engineering, Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India.

Research Article

International Journal of Science and Research Archive, 2025, 15(01), 1730-1735

Article DOI: 10.30574/ijsra.2025.15.1.1255

DOI url: https://doi.org/10.30574/ijsra.2025.15.1.1255

Received on 18 February 2025; revised on 27 April 2025; accepted on 30 April 2025

Cloud platforms are ever more vulnerable to advanced cyber threats, which demand intelligent and self-reliant security systems. We introduce CloudShield, a prototype Agentic AI system for mimicking live cloud data protection in Azure platforms. The system mimics round-the-clock log collection in Azure-type protocols, employs the Isolation Forest algorithm to identify outliers, and responds automatically to attacks such as brute-force attacks and malware. Logs are locally stored in a SQLite database, encrypted for secure storage, and can be deployed entirely self-contained without dependencies. CloudShield includes an interactive real-time dashboard for threat visualization and system analysis. Its agent-based, modular architecture supports scalability, automation, and high detection rates—making it a strong experimental model for current cloud security research.

Cloud Security; Agentic AI; Anomaly Detection; Isolation Forest; Azure Logs; Automated Response

https://ijsra.net/sites/default/files/fulltext_pdf/IJSRA-2025-1255.pdf

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Naseer R, Srujan K M, Deepthi A S, Divyashree C H and Goutham M. Framework for Cloud Data Security Using Agentic AI. International Journal of Science and Research Archive, 2025, 15(01), 1730-1735. Article DOI: https://doi.org/10.30574/ijsra.2025.15.1.1255.

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

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