Department of Computer Science & Engineering, Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India.
International Journal of Science and Research Archive, 2025, 15(01), 1730-1735
Article DOI: 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
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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 © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0







