Framework for Cloud Data Security Using Agentic AI
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.
Institutions
- Bapuji Dental College and Hospital (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-30
- DOI
- https://doi.org/10.5281/zenodo.17150337
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00