Adaptive AI Cybersecurity Frameworks for Healthcare Cloud Governance and Patient Data Protection
DOI:
https://doi.org/10.21590/Keywords:
Adaptive AI, Healthcare Cybersecurity, Cloud Governance, Patient Data Protection, Artificial Intelligence, Cloud Computing, Machine Learning, Healthcare Cloud Security, Threat Intelligence, Zero Trust Architecture, Electronic Health Records, Predictive Analytics, Identity and Access Management, Data Privacy, Security Information and Event Management.Abstract
The rapid digital transformation of healthcare systems has accelerated the adoption of cloud computing, electronic health records, telemedicine, and artificial intelligence technologies. While these innovations improve healthcare accessibility, operational efficiency, and clinical decision-making, they also introduce serious cybersecurity risks associated with patient data privacy, unauthorized access, ransomware attacks, and cloud vulnerabilities. This study examines adaptive AI cybersecurity frameworks designed for healthcare cloud governance and patient data protection. The research explores how artificial intelligence, machine learning, behavioral analytics, and automated threat intelligence systems strengthen healthcare cybersecurity infrastructures in cloud-based environments. The study further investigates the role of adaptive security models in identifying cyber threats, detecting anomalies, managing access controls, and ensuring compliance with healthcare regulations such as HIPAA and GDPR. Technologies including zero-trust architecture, encryption systems, Security Information and Event Management platforms, identity and access management, and predictive threat analytics are analyzed as critical components of healthcare cloud governance. A qualitative and analytical research methodology is employed to evaluate existing cybersecurity frameworks, implementation strategies, and operational challenges within healthcare organizations. The findings reveal that adaptive AI-driven cybersecurity significantly enhances patient data security, improves threat response efficiency, and strengthens healthcare cloud resilience. The study concludes that intelligent and adaptive cybersecurity frameworks are essential for maintaining trust, privacy, regulatory compliance, and operational continuity within modern digital healthcare ecosystems.
References
1. Raja, G. V. (2023). Modernizing Enterprise Systems using AI with Machine Learning and Cloud Computing for Intelligent Systems. International Journal of Future Innovative Science and Technology (IJFIST), 6(6), 11713.
2. Garg, D. (2025). Warehouse Management System with IoT: A Comprehensive Guide. INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY, 16, 2320-2332.
3. Ambalakannu, M. (2025). Accelerating Claims Processing with Observability and Automated Dashboards. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 8(3), 12179-12186.
4. Rahman, M. W., & Hossain, M. S. (2024). An Explainable AI Framework for Insider Threat Detection Using Behavioral Business Analytics. An Explainable AI Framework for Insider Threat Detection Using Behavioral Business Analytics, 1(8), 70-97.
5. Vani, S., Malathi, P., Ramya, V. J., Sriman, B., Saravanan, M., & Srivel, R. (2024). An efficient black widow optimization-based faster R-CNN for classification of COVID-19 from CT images. Multimedia Systems, 30(2), 108.
6. Gopinathan, V. R. (2025). Design and Implementation of Scalable Distributed Machine Learning in Multi-Cloud Infrastructures. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 8(5), 17211.
7. Bansal, D. K. (2025). Enterprise data engineering: architecting modern data warehouses for business success. Int J Sci Res Comput Sci Eng Inf Technol, 11(1), 3266-77.
8. Sugumar, R. (2024). Quantum-Resilient Cryptographic Protocols for the Next-Generation Financial Cybersecurity Landscape. International Journal of Humanities and Information Technology, 6(02), 89-105.
9. Karvannan, R. (2023). Empowering healthcare operations with next-generation compliance and inventory solutions. International Journal of Engineering & Extended Technologies Research (IJEETR), 5(4), 297-313.
10. Appani, C. (2024). Explainable AI for fraud detection in financial transactions. Journal of Information Systems Engineering and Management, 9(3). https://jisem-journal.com/download/32_Explainable_AI_for_Fraud_Detection.pdf
11. Bellundagi, M. (2024). Integrating Decision Intelligence and Business Rules Management for Enterprise Applications. International Journal of Research and Applied Innovations, 7(3), 10765-10773.
12. Cherukuri, B. R., & Arulkumar, V. (2024, February). Optimization of Data Structures and Trade-Offs with Concurrency Control in Multithread Software Structures Using Artificial Intelligence. In 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT) (Vol. 5, pp. 1860-1865). IEEE.
13. Mathew, A. (2024). Cloud data sovereignty governance and risk implications of cross-border cloud storage. Information Systems Audit and Control Association.
14. Suddala, V. R. A. K. (2024). Machine learning for operational excellence: Real-world applications. International Journal of Future Innovative Science and Technology (IJFIST), 7(6), 13908–13917. https://doi.org/10.15662/IJFIST.2024.0706010
15. Jayalakshmi, D., Vimal, V. R., Loganayagi, S., Narayanan, L. K., & Hemavathi, R. (2024, November). Enhancing supply chain efficiency with IoT and data analytics. In 2024 International Conference on Recent Advances in Science and Engineering Technology (ICRASET) (pp. 1-5). IEEE.
16. Adepu, G. (2021). AI-enabled digital identity verification framework for government self-service platforms using secure API and cloud integration. International Journal of Research Publications in Engineering, Technology and Management, 4(1), 160–176.
17. Pothuri, M. K. (2025). The role of data governance in achieving compliance and trust in healthcare and fintech. IJAIDR–Journal of Advances in Developmental Research, 16(2).
18. Pothireddy, S. R. (2024). Secure AI Adoption: Governance Models for Copilot in Healthcare and Non-Profit Enterprises. International Journal of Computer Technology and Electronics Communication, 7(4), 9212-9222.
19. Shewale, V. (2025). The Ethics of Cybersecurity: Balancing Security and Privacy in the Digital Age. European Journal of Computer Science and Information Technology, 13(15), 11-20.
20. Bheemisetty, N. (2024). AI-Powered Recommendation Systems Best Practices and Real-World Applications. International Journal of Future Innovative Science and Technology (IJFIST), 7(6), 13926.
21. Sengupta, J., & Alzbutas, R. (2022). Intracranial hemorrhages segmentation and features selection applying cuckoo search algorithm with gated recurrent unit. Applied Sciences, 12(21), 10851.
22. Ganesan M. (2025). Artificial intelligence AI driven proactive customer service excellence platform in e commerce industry. International Journal of Computer Technology and Electronics Communication 8(1) 10089–10099.
23. Balamuralidhar Sarabu, V. (2023). Designing controlled data migration pipelines from on-premises to cloud platforms for mission-critical enterprise systems. International Journal of Engineering & Extended Technologies Research (IJEETR), 5(5), 13–33.
24. Pasumarthi, H. (2023). Applying machine learning to high-volume banking platforms: From transaction data to predictive risk intelligence. International Journal of Artificial Intelligence & Machine Learning, 2(1), 356–370. https://doi.org/10.34218/IJAIML_02_01_029
25. Rongali, L.P., (2025). Continuous Integration and Continuous Delivery (CI/CD) pipelines: Explore how DevOps practices ensure seamless integration and delivery of AI models. International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), 5(1), pp.278–286. DOI: 10.48175/IJARSCT-23240. ISSN: 2581-9429.
26. Panyala, V. R. (2024). Architecting autonomous cloud platforms with AI-driven self-optimization capabilities. International Journal of Research Publications in Engineering, Technology and Management, 7(1), 10000–10003.
27. Ambalakannu, M. (2024). The emergence of AI-powered data analytics revolutionizing business intelligence. International Journal of Future Innovative Science and Technology (IJFIST), 7(6), 13955.
28. Mallireddy, S. (2024). Economic impact of ServiceNow among financial institutions. International Journal of Research and Applied Innovations, 7(3), 1–7.
29. Lanka, S. (2023). Blurring boundaries where artificial intelligence ends and human potential begins. International Journal of Computer Technology and Electronics Communication, 6(4), 7331-7341.
30. Narayanan, S. (2024). Authenticity assurance architecture: A multi-layer organizational deepfake threat taxonomy and control framework. World Journal of Advanced Research and Reviews, 24(3), 3639–3647. https://philarchive.org/archive/NARAAA-3
31. Kassetty, N., ALANG, K. S., & Kandula, S. R. (2024). Green Finance and Fintech in Banking: Assessing Their Synergistic Impact on Environmental Performance. International Journal of Global Innovations and Solutions (IJGIS).
32. Soundappan, S. J. (2025). Self-Adaptive Predictive Analytics Frameworks using Reinforcement Learning and Federated Cloud Intelligence. International Journal of Research and Applied Innovations, 8(4), 12711-12723.
33. Indurthy, V. S. K. (2024). The surge in AI-powered data analytics revolutionizing business intelligence. International Journal of Future Innovative Science and Technology (IJFIST), 7(6), 13964.
34. Suvvari, S. K. (2023). Shift Left: Moving the Inclusion of Accessibility Functionalities to the Left in Agile Product Development Life Cycle. Journal of Computational Analysis and Applications, 31(4).
35. Rahman, M. B., Yasin, M., & Ahmed, M. P. (2024). Data-Driven Population Health Analytics for Identifying High-Risk Groups and Health Disparities. American Journal Of Botany And Bioengineering, 1(11), 58-82.
36. Tailor, P., & Kale, A. (2025). Multimodal sentiment analysis of earnings calls and SEC filings: A deep learning approach to financial disclosures. Utilitas Mathematica, 122, 3163-3168.
37. Lanka, S. (2022). Building smarter security systems with AI: Inside Citrix analytics for security. Journal of Advanced Research Engineering and Technology (JARET), 1(2), 93–109. https://doi.org/10.34218/JARET_01_02_009
38. Adepu, R. (2024). Secure cloud migration strategies for enterprise data center modernization. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(6), 239–258.
39. Suddala, V. R. A. K. (2025). Healthcare e-commerce platforms driving secure, scalable, and auditable service delivery. International Journal of Engineering & Extended Technologies Research (IJEETR), 7(1), 9340–9351.
40. Navas, V. M. T., Buljac, A., Hild, F., Morgeneyer, T., Helfen, L., Bernacki, M., & Bouchard, P. O. (2019). A comparative study of image segmentation methods for micromechanical simulations of ductile damage. Computational Materials Science, 159, 43-65.
41. Prasad, P. K. (2024). AI-driven cloud governance 2.0: Balancing agility, compliance, and operational efficiency in hybrid multi-cloud environments. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(2), 7848–7851.
