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Intelligent Enterprise Data Platforms using Retrieval-Augmented AI and Secure Multi-Cloud Integration Frameworks

Dr. Pankaj Pratap Singh

Assistant Professor, Department of Computer Science and Engineering, Central Institute of Technology, Assam, India

Abstract

Cloud computing environments are increasingly complex due to the adoption of multi-cloud architectures, containerized applications, distributed workloads, and dynamically provisioned infrastructure. These environments introduce security challenges associated with misconfigured resources, excessive permissions, exposed services, inconsistent security policies, and violations of regulatory requirements. Traditional cloud security posture management approaches primarily depend on predefined rules, manual assessments, and periodic compliance audits, which may be insufficient for identifying evolving configuration risks. This research investigates an artificial intelligence-driven cloud security posture management framework that integrates intelligent configuration analysis, contextual risk assessment, and automated compliance enforcement. The proposed framework analyzes cloud resource configurations, identity and access management policies, network security rules, storage permissions, encryption settings, and workload deployment parameters to identify security weaknesses and prioritize remediation activities. Machine learning techniques support anomaly detection and risk classification, while policy-based automation facilitates corrective actions aligned with organizational security requirements. The methodology employs a controlled experimental environment to compare the proposed framework with conventional rule-based security assessment mechanisms. Evaluation metrics include misconfiguration detection accuracy, compliance coverage, false-positive rates, remediation time, and operational overhead. The research aims to establish an integrated approach that improves security visibility, accelerates compliance verification, and reduces configuration-related exposure across heterogeneous cloud infrastructures. The resulting framework provides a foundation for adaptive, scalable, and continuously monitored cloud security posture management

Article Information

Journal

International Journal of Science, Research and Technology

Volume (Issue)

Vol. 8 No. 5 (2025): International Journal of Science, Research and Technology (IJSRAT)

DOI

https://doi.org/10.15662/IJSRAT.2025.0805010

Pages

14702-14711

Published

October 22, 2025
Copyright

Open Access

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

How to Cite

Dr. Pankaj Pratap Singh (%2025). Intelligent Enterprise Data Platforms using Retrieval-Augmented AI and Secure Multi-Cloud Integration Frameworks. International Journal of Science, Research and Technology , Vol. 8 No. 5 (2025): International Journal of Science, Research and Technology (IJSRAT) , pp. 14702-14711. https://doi.org/10.15662/IJSRAT.2025.0805010

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