A Secure API-Enabled Cloud Platform for Healthcare and Financial Systems Leveraging AI and Apache-Based Real-Time Analytics

Johnson Sammel Christopher

doi:10.15662/IJRAI.2024.0704007

Authors

Johnson Sammel Christopher Senior Team Lead, CTS, United Kingdom Author

DOI:

https://doi.org/10.15662/IJRAI.2024.0704007

Keywords:

AI-powered cloud, API-driven architecture, Real-time analytics, Healthcare systems, Financial systems, Cybersecurity, Apache-based frameworks

Abstract

The widespread adoption of cloud computing in the healthcare and financial sectors has enabled real-time data processing and analytics, but it has also increased exposure to cybersecurity threats. This paper introduces an AI-powered, API-driven cloud platform designed to deliver secure, real-time analytics for healthcare and financial systems using Apache-based frameworks. The proposed architecture combines scalable APIs, microservices, and cloud-native design principles to support high-throughput data ingestion, processing, and machine learning-driven analytics. Embedded AI models provide predictive insights, anomaly detection, and real-time decision support while ensuring data confidentiality and integrity. Security mechanisms—including encryption, access controls, and continuous monitoring—are implemented to maintain compliance with healthcare regulations (e.g., HIPAA) and financial industry standards. Experimental evaluation shows that the platform achieves low-latency processing, accurate threat detection, and high availability, outperforming traditional batch-processing systems. The results demonstrate that API-driven, AI-enabled cloud architectures leveraging Apache technologies offer a robust, scalable, and secure foundation for integrating real-time analytics into mission-critical healthcare and financial applications.

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