Cloud-Enabled Federated AI Pipelines for Financial Cyber Risk Management and Security in Healthcare Using Data Analytics
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Abstract
Cloud computing and distributed data systems have significantly enhanced analytics-driven decision-making in the financial sector, yet they also introduce critical cybersecurity risks such as data breaches, fraud, and regulatory compliance challenges. This paper proposes Cloud-Enabled Federated AI Pipelines for Financial Cyber Risk Management and Security in Healthcare, a framework designed to deliver scalable, privacy-preserving, and intelligent cybersecurity solutions. The framework employs federated learning to enable collaborative AI model training across multiple cloud and on-premise data sources while safeguarding sensitive information. AI-powered analytics detect anomalies, predict potential cyber threats, and facilitate proactive risk mitigation in real-time. Comprehensive security measures, including encryption, access control, and compliance monitoring, ensure alignment with regulatory standards such as HIPAA, PCI-DSS, and GDPR. Experimental evaluations demonstrate enhanced threat detection accuracy, reduced response latency, and robust cybersecurity for cloud-hosted financial operations integrated with healthcare systems. This framework provides a secure, scalable, and intelligent solution for managing complex cyber risks in multi-institutional cloud environments.
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