An Optimized System Design for Privacy-Preserving Blockchain Adoption and Autonomous Compliance Management in Cloud-Enabled Healthcare and Financial Infrastructure
Keywords:
Blockchain, Cloud Computing, Healthcare Systems, Financial InfrastructureAbstract
The increasing convergence of healthcare and financial systems with cloud computing has introduced significant challenges related to data privacy, interoperability, regulatory compliance, and secure data exchange. Traditional centralized architectures struggle to ensure trust, transparency, and scalability in environments characterized by sensitive personal and institutional data. Blockchain technology has emerged as a promising paradigm to address these limitations by enabling decentralized trust, immutable auditability, and cryptographically secured transactions. However, its integration into cloud-assisted healthcare and financial infrastructures raises new concerns related to scalability, privacy preservation, and compliance automation.
This study proposes an optimized system design that integrates blockchain-based security mechanisms, privacy-preserving protocols, and autonomous compliance management within cloud-enabled healthcare and financial ecosystems. The proposed architecture synthesizes insights from existing literature on cloud security, privacy-preserving data sharing, and blockchain-enabled healthcare systems. A key focus is placed on secure electronic health record (EHR) systems using blockchain, as demonstrated by Kim et al. (2020), which forms the foundational reference model for secure protocol design and decentralized data integrity assurance.
The study further introduces a multi-layered framework consisting of blockchain consensus layers, privacy-enhancing computation modules, and compliance automation engines capable of enforcing regulatory standards such as HIPAA-like policies through programmable audit trails. Findings indicate that integrating blockchain with cloud systems enhances data
integrity, reduces unauthorized access risks, and improves compliance traceability, while also introducing computational overhead and interoperability constraints.
The proposed model contributes to advancing secure digital infrastructure design for healthcare and financial sectors by offering a scalable, privacy-preserving, and compliance-aware system architecture suitable for next-generation distributed environments.
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References
1. Al-Issa Y, Ottom MA, Tamrawi A. eHealth Cloud Security Challenges: A Survey. J Healthc Eng. 2019;2019:7516035.
2. Behl A. Emerging security challenges in cloud computing: An insight to cloud security challenges and their mitigation. 2011 World Congress on Information and Communication Technologies. IEEE; 2011.
3. Dong X, Yu J, Luo Y, Chen Y, Xue G, Li M. Achieving a practical, scalable and privacy-preserving data sharing service in cloud computing. Comput. Sec. 2014;42:151–164.
4. Hoeseb CH, Tanner M. Large-Scale Agile Implementation in Large Financial Institutions: A Systematic Literature Review. Proceedings of the 2020 International Conference on Computational Science and Computational Intelligence (CSCI). 2020.
5. Kim M, Yu S, Lee J, Park Y, Park Y. Design of Secure Protocol for Cloud-Assisted Electronic Health Record System Using Blockchain. Sensors (Basel, Switzerland). 2020;20(10).
6. Hebbar, K. S., Sharma, V., &Maheshkar, J. A. (2026). Edge-AI microservice orchestration for private, real-time generative FinTech applications. Future Technology, 5(2), 13–24. https://doi.org/10.55670/fpll.futech.5.2.2
7. K. Bhat and G. Krishnan, "A Review of Artificial Intelligence in Finance: Driving the Next Wave of Industry Innovation," 2025 3rd International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI), Coimbatore, India, 2025, pp. 2033-2040, doi: 10.1109/ICoICI65217.2025.11252894.
8. Karim, A. S. A. (2025). MITIGATING ELECTROMAGNETIC INTERFERENCE IN 10G AUTOMOTIVE ETHERNET: HYPERLYNX-VALIDATED SHIELDING FOR CAMERA PCB DESIGN IN ADAS LIGHTING CONTROL. International Journal of Apllied Mathematics, 38(2s), 1257–1268. https://doi.org/10.12732/ijam.v38i2s.718
9. Anjali Kale. (2025). Environmental Accounting: A Strategic Tool for Sustainable Development. European Economic Letters (EEL), 15(4), 2269–2276. https://doi.org/10.52783/eel.v15i4.4050
10. Liu Q, Chan K-C, Chimhundu R. Fintech research: systematic mapping, classification, and future directions. Financial Innovation. 2024;10:Article 24.
11. Mrozek D. A review of Cloud computing technologies for comprehensive microRNA analyses. Computational biology and chemistry. 2020;88:107365.
12. Mohammed Nayeem (2025). Strategic Cybersecurity Governance: A Risk-Based Policy Framework for IT Protection and Compliance. In Proceedings of the International Conference on Artificial Intelligence and Cybersecurity (ICAIC 2025), 19 - 29.
13. Ravilla, H. (2025). Building Scalable Applications with Heroku and Salesforce Integration. American Journal of Technology, 4(3), 15–36. https://doi.org/10.58425/ajt.v4i3.454
14. Sajid A, Abbas H. Data Privacy in Cloud-assisted Healthcare Systems: State of the Art and Future Challenges. Journal of medical systems. 2016;40(6):155.
15. Sagar Kesarpu. (2025). Chaos Engineering as a Learning Framework: A Human-Centered Model for Developing High-Reliability Engineering Teams. The American Journal of Engineering and Technology, 7(12), 57–64. https://doi.org/10.37547/tajet/Volume07Issue12-05
16. Sisodiya VS, Garg H. A Comprehensive Study of Blockchain and its Various Applications. IEEE Xplore. 2023.
17. J. Singh, “Analytical Study of Challenges and Opportunities for Business Analysts in Emerging Economies Amidst AI and Automation for Evolving Skill Requirements,” European Journal of Business and Management Research, vol. 11, no. 1, pp. 107–112, Feb. 2026, doi: 10.24018/ejbmr.2026.11.1.52852.
18. Varanasi, S. R. (2025b). HIPAA-AS-Code: Automated Audit Trails in AWS Sage Maker Pipelines. European Journal of Engineering and Technology Research, 10(5), 23–26.
19. V. S. N. Kanikanti, S. K. Tiwari, V. Nayan, S. Suryawanshi, V. Banerjee and I. E. Ahmed, "Deep Q-Learning Driven Dynamic Optimal Task Scheduling for Cloud Computing Using Optimal Queuing," 2025 10th International Conference on Information Technology Trends (ITT), Dubai, United Arab Emirates, 2025, pp. 112-117, doi: 10.1109/ITT69610.2025.11352940.
20. Wooten R, Klink R, Sinek F, Bai Y, Sharma M. Design and implementation of a secure healthcare social cloud system. 2012 12Th IEEE/ACM Int. Symp. Cluster, Cloud Grid Comput. (Ccgrid 2012). 2012:805–810.
21. Yang J, Li J, Niu Y. A hybrid solution for privacy-preserving medical data sharing in the cloud environment. Futur. Gener. Comput. Syst. 2015;43–44:74–86.
22. Zhang Q, Wang X, Yuan J, Liu L, Wang R, Huang H, Li Y. A hierarchical group key agreement protocol using orientable attributes for cloud computing. Inform. Sci. 2019;480:55–69.
23. Zhou J, Cao Z, Dong X, Xiong N, Vasilakos A. 4S: A secure and privacy-preserving key management scheme for cloud-assisted wireless body area network in m-healthcare social networks. Inf. Sci. 2015;314:255–276.
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