An Intelligent Zero-Trust Security Framework for AI-Driven Access Governance and Adaptive Policy Orchestration in Hybrid Cloud Enterprise Environments

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Dr. Jamal-Deen Abdulai

Abstract

The rapid adoption of hybrid cloud computing has transformed enterprise infrastructure by integrating private data centers, public cloud platforms, and distributed digital services. However, this transformation introduces complex security challenges involving identity management, unauthorized access, inconsistent policy enforcement, and evolving cyber threats. Traditional perimeter-based security mechanisms are insufficient for protecting dynamic enterprise environments in which users, applications, devices, and workloads continuously interact across multiple infrastructure boundaries. This research proposes an integrated framework combining Zero-Trust Access Control (ZTAC) with Artificial Intelligence (AI)-based security policy management to strengthen enterprise security across hybrid cloud systems. The proposed framework incorporates continuous identity verification, contextual access evaluation, behavioral anomaly detection, risk-based authorization, and automated policy adaptation. Machine learning models analyze user behavior, device posture, network activity, and resource sensitivity to identify potential threats and support dynamic access decisions. A centralized policy orchestration component coordinates security rules across heterogeneous cloud platforms while maintaining consistent enforcement and auditability. The research methodology adopts a comparative evaluation approach using security, operational, and performance indicators, including unauthorized access detection, false-positive rate, policy enforcement latency, and resource utilization. The framework is intended to improve threat detection, reduce excessive privileges, and support scalable security governance. Its effectiveness must be established through reproducible experiments and comparison with conventional access control mechanisms. The study contributes a structured approach to integrating adaptive intelligence with Zero-Trust principles for resilient, transparent, and continuously monitored hybrid cloud enterprise security.
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How to Cite

An Intelligent Zero-Trust Security Framework for AI-Driven Access Governance and Adaptive Policy Orchestration in Hybrid Cloud Enterprise Environments. (2024). International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(5), 11408-11416. https://doi.org/10.15662/IJRPETM.2024.0705026

References

1. Hong, J. B., Nhlabatsi, A., Kim, D. S., Hussein, A., Fetais, N., & Khan, K. M. (2019). Systematic identification of threats in the cloud: A survey. Computer Networks, 150, 46–69. https://doi.org/10.1016/j.comnet.2018.12.009

2. Gassais, R., Ezzati-Jivan, N., Fernandez, J. M., Aloise, D., & Dagenais, M. R. (2020). Multi-level host-based intrusion detection system for Internet of things. Journal of Cloud Computing, 9, Article 62. https://doi.org/10.1186/s13677-020-00206-6

3. Venkatasalam, K., Rajendran, P., & Thangavel, M. (2019). Improving the accuracy of feature selection in big data mining using accelerated flower pollination (AFP) algorithm. Journal of medical systems, 43(4), 96.

4. Karrothu, A. (2024). Automated risk-based security controls for vulnerability detection and prevention across cloud-native software development lifecycles. International Journal of Humanities and Information Technology, 6(03), 147–166.

5. Polamarasetty, V. K. (2023). Modern enterprise HR technology through Workday-based benefits and absence management. International Journal of Engineering & Extended Technologies Research (IJEETR), 5(4), 6908–6913.

6. Mounika, B., & Thota, S. (2021). A Multilayer Cloud–AI Framework for Intelligent Process Automation in Salesforce-Centric Digital Enterprises. International Journal of AI, BigData, Computational and Management Studies, 2(3), 99-109.

7. Aesha, U. H., Bhuiyan, R. H., Jabeer, M. A., & Khan, S. M. (2024). AI-Driven Predictive Maintenance for Manufacturing and Aerospace Systems. Journal of Mechanical, Civil and Industrial Engineering, 5(1), 50-72.

8. Jinna, K. R., & Subramani, S. K. (2022). Supply-chain-aware CI/CD for regulated enterprises: Integrating artifact signing, secret injection and promotion gates in Kubernetes-native pipelines. International Journal of Computer Technology and Electronics Communication, 5(6), 16275-16285.

9. Mathew, A. R. (2019). Cyber-infrastructure connections and smart gird security. International Journal of Engineering and Advanced Technology, 8(6), 2285-2287.

10. Shaik, N. (2024). AI-driven scheduling for multi-cloud Kubernetes: Lessons from enterprise deployment. International Journal of Research and Applied Innovations, 7(3), 10880–10891.

11. Bandari, U., & Kondisetty, K. (2022). Privacy by architecture: Operationalizing GDPR records of processing activities and right-to-erasure in enterprise analytics platforms. International Journal of Humanities and Information Technology, 4(1–3), 342–351.

12. Chandran, A. S. (2023). A unified Spark ETL stack across Cloudera CDP, Azure HDInsight, and Databricks. International Journal of Computer Technology and Electronics Communication, 6(6), 8207–8217.

13. Kalakoti, M. K. R. (2022). Dependency-aware migration and resilience validation of stateful applications to enterprise cloud. International Journal of Research Publications in Engineering, Technology and Management, 5(2), 6582–6590.

14. Chy, M. S. K., Enaye, M. A., Alam, A., Gazi, M. S., Siddique, M. T., Tasnim, M., & Sultana, S. (2024). Data-Driven Adaptive AI Cyber Defense: A Comparative Analysis of Machine Learning Classifiers for Malware and APT Detection. International Journal of Research and Applied Innovations, 7(4), 11217-11226.

15. Valavala, S. K. (2023). Applying zero trust to financial microservices through default deny authorization. International Journal of Engineering & Extended Technologies Research, 5(3), 6627–6637.

16. Padmanabham, S. (2022). Secure enterprise architecture for pharmacy benefit management platforms. International Journal of Engineering & Extended Technologies Research (IJEETR), 4(5), 5381-5386.

17. Puli, S. K. (2022). An Event-Driven Canonical Data Architecture for Integrating Microsoft Dynamics 365 Customer and Dealer Data with On-Premises Enterprise Systems. European Journal of Advances in Engineering and Technology, 9(1), 105-114.

18. Karuturi, Y. (2023). Energy-aware capacity governance for large-scale SAP HANA deployments. International Journal of Research and Applied Innovations, 6(3), 6000–6009.

19. Ahuja, D. (2023). Multi-cloud management strategies: Tools, challenges, and implementation methods. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, 9(10), 493-506.

20. Gantikota, S. (2023). Reducing HL7 Processing Errors through Automated File Creation and Ingestion Pipelines: A Production Case Study in EHR Data Integration. International Journal of Emerging Trends in Computer Science and Information Technology, 4(4), 241-245.

21. Chinthamani, R. (2024). Modernizing enterprise workload identity through SPIFFE-based certificate automation. International Journal of Research and Applied Innovations, 7(4), 11240–11245.

22. Madhan, E. S., Kannan, K. S., Rani, P. S., Rani, J. V., & Anguraj, D. K. (2021). A distributed submerged object detection and classification enhancement with deep learning. Distrib. Parallel Databases, 41, 1-17.

23. Ramasamy, M. (2022). Closed-loop network automation: Architectural principles from Catalyst Center-scale systems. International Journal of Humanities and Information Technology, 4(1–3), 302–313.

24. Vemireddy, S. (2023). Engineering regulatory-aware data processing systems for tax advisory platforms. International Journal of Science, Research and Technology, 6(1), 9243–9249.

25. Mysula, S. (2024). Event-driven integration architecture using publication methods for real-time DealCloud business operations & workflows. International Journal of Research and Applied Innovations, 7(4), 11233–11239.

26. Reddy, K. V. (2022). Power-aware verification closure using AI-enhanced UVM and dynamic voltage and frequency scaling models. International Journal of Research and Applied Innovations, 5(4), 7424–7436.

27. Selvarajan, K. (2023). Optimizing large-scale data lakehouse architectures for performance and cost efficiency. International Journal of Research and Applied Innovations, 6(6), 10093–10101.

28. Basavala, S. R. (2024). Zero trust API security architecture for microservices-based enterprise applications. International Journal of Computer Technology and Electronics Communication, 7(4), 9269–9280.

29. Katakam, R. (2023). Automated loan processing and payment reconciliation through integrated banking workflows. International Journal of Engineering & Extended Technologies Research, 5(5), 7313–7324.

30. Neela, S. (2023). Resilient middleware ecosystems: Integrating fault tolerance, recovery-oriented design, and observability for real-time enterprise integration. International Journal of Emerging Research in Engineering and Technology, 4(1), 186–189. https://doi.org/10.63282/3050-922X.IJERET-V4I1P120

31. Kopparthi, G. S. (2023). Trustworthy artificial intelligence for high-stakes decision-making: Explainability, human oversight, and system reliability. International Journal of Engineering & Extended Technologies Research, 5(4), 6979–6992.

32. Mudunuri, P. R. (2023). Governance-aware infrastructure-as-code for regulated research environments. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(4), 9017-9027.

33. Kalabhavi, V. (2024). Promotional spend analytics using AI for PFME allocation and coupon redemption optimization. International Journal of Research Publications in Engineering, Technology and Management, 7(2), 10417–10429.

34. Yadavalli, V. R. (2023). Cutover intelligence mesh: A dependency-aware architecture for enterprise cloud ERP migration. International Journal of Computer Technology and Electronics Communication, 6(4), 7400–7416.

35. Natta, P. K. (2022). Computer-vision-assisted retail inventory automation: Integrating autonomous scan data with worklist completion systems. International Journal of Science, Research and Technology, 5(6), 8957–8969.

36. Randhi, K. S. (2022). A scalable integration framework for enterprise application metadata aggregation and synchronization. International Journal of Research Publications in Engineering, Technology and Management, 5(2), 6564–6581.

37. Gadige, C. D. (2023). Secure CRM modernization: Architectural patterns for migrating enterprise customer data from legacy CRM platforms to Salesforce. International Journal of Computer Technology and Electronics Communication, 6(3), 7013–702