Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{191686,
        author = {Pratishtha Arora and Penina Tripathi and Himanshi Parihar},
        title = {The Unified Adaptive Security (UAS)-Cloud Framework: An Ai-Driven Approach to Cloud Security and Data Protection in Shared Multi-Cloud Environments},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {13-24},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191686},
        abstract = {As the global reliance on cloud computing intensifies, driven by the need for scalability, agility, and the adoption of multi-cloud architectures, the secure management of distributed data and ensuring cross-platform interoperability have emerged as paramount and complex challenges. Conventional cloud security practices—which rely on fragmented, separately applied mechanisms such as static encryption, traditional access control, and siloed Zero-Trust Architecture (ZTA) implementations—result in inconsistent security posture, policy sprawl, increased operational latency, and highly inefficient security orchestration. Furthermore, the absence of a unified, converged security model capable of continuously adapting to real-time, context-based risk factors significantly contributes to the threat surface vulnerability inherent in complex multi-tenant cloud environments.
This paper introduces the UAS-Cloud (Unified Adaptive Security Framework), a novel, AI-enhanced security solution designed to resolve these persistent issues. UAS-Cloud converges three fundamental security controls—a Centralized Key Management System (CKMS), an Adaptive Policy Engine (APE), and a Zero-Trust enforced API Gateway—into a singular, highly interoperable security layer. The core innovation lies in the Adaptive Policy Engine, which uses machine learning to enable automated, real-time, risk-based access decisions, robust encryption governance, and seamless cross-platform policy compatibility. By integrating intelligent security automation, UAS-Cloud substantially increases system throughput, reduces transaction latency, and achieves security consistency across heterogeneous cloud platforms, thereby establishing a blueprint for future-ready, resilient cloud security architectures.},
        keywords = {Access Control, Adaptive Policy Engine, Cloud Security, Encryption, Key Management, Multi-Cloud, Security Orchestration, Zero-Trust.},
        month = {},
        }