Secure Financial AI-Powered Federated Architecture for Healthcare and Banking Cybersecurity on AWS Cloud
DOI:
https://doi.org/10.15680/IJCTECE.2023.0606018Keywords:
Financial Systems, Banking, Healthcare, AI, Federated Learning, AWS Cloud, CybersecurityAbstract
The rapid adoption of cloud computing in the healthcare and banking sectors has significantly enhanced operational efficiency, data-driven decision-making, and digital services. However, these advancements also introduce complex cybersecurity challenges, including data breaches, insider threats, fraud, and regulatory compliance risks. This paper proposes a Secure Financial AI-Powered Federated Architecture for Healthcare and Banking Cybersecurity on AWS Cloud, a framework designed to provide scalable, privacy-preserving, and intelligent cybersecurity solutions. The proposed architecture leverages federated learning to collaboratively train AI models across distributed healthcare and banking datasets without sharing sensitive raw data, ensuring data privacy and compliance with regulatory standards such as HIPAA, PCI-DSS, and GDPR. Cloud-native services on AWS are utilized to support real-time threat detection, anomaly identification, and proactive cyber risk mitigation. Security mechanisms including encryption, access control, and continuous compliance monitoring are integrated throughout the architecture. Experimental results demonstrate improved detection accuracy, reduced response latency, and enhanced protection against emerging cyber threats, establishing a robust solution for multi-institutional cloud cybersecurity management.
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