Cybersecurity Aware Cloud Native AI Framework for Scalable Healthcare Data Analytics via APIs
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Abstract
The accelerating digitalization of critical sectors such as healthcare and waste management has resulted in the exponential growth of sensitive and diverse data, creating a strong demand for secure, scalable, and intelligent analytics solutions. This study presents a Cybersecurity-Driven Cloud-Native Financial AI Architecture aimed at enabling secure and efficient data analytics across healthcare and waste management domains. The proposed architecture combines cloud-native microservices, secure API-based communication, and financial AI modules with robust cybersecurity measures, including encryption, fine-grained access control, and continuous threat detection. By supporting real-time data ingestion, automated risk evaluation, and intelligent decision-making, the framework strengthens data confidentiality, integrity, and availability while facilitating seamless cross-domain analytics. Experimental results indicate enhanced system resilience, lower processing latency, and improved analytical performance when compared to conventional monolithic architectures. Overall, the proposed solution provides a scalable, interoperable, and secure foundation for analytics in data-intensive and security-critical environments.
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