An Intelligent AI–Cloud Machine Learning Framework for Cybersecurity in SAP Financial and Healthcare Systems
DOI:
https://doi.org/10.15662/IJARCST.2024.0701812Keywords:
AI–Cloud Computing, Machine Learning, SAP Security, Cybersecurity Framework, Financial Systems, Healthcare Systems, Risk ManagementAbstract
The increasing reliance on SAP-based cloud platforms in financial and healthcare organizations has accelerated digital transformation while simultaneously expanding the cyber attack surface. Sensitive financial transactions and electronic health records processed through SAP environments are frequent targets of cyber threats such as fraud, ransomware, insider attacks, and advanced persistent threats. Conventional security mechanisms are often insufficient to address the scale, complexity, and dynamic nature of these risks. To overcome these challenges, this paper proposes a Secure AI–Cloud Machine Learning Framework for Financial and Healthcare Cybersecurity in SAP Environments. The proposed framework integrates cloud-native AI and machine learning capabilities with SAP platforms, including SAP S/4HANA and SAP Business Technology Platform (BTP), to enable intelligent threat detection, risk analysis, and automated response. Machine learning models analyze SAP application logs, transactional data, user behavior, and network telemetry to identify anomalies and malicious activities in real time. The framework adopts a zero-trust security model, incorporates threat intelligence feeds, and supports continuous compliance with regulatory standards such as PCI-DSS, HIPAA, SOX, and GDPR. Experimental evaluation and SAP-centric use cases demonstrate improved detection accuracy, reduced incident response time, and enhanced visibility into cybersecurity risks across hybrid and multi-cloud SAP landscapes. The proposed approach offers a scalable, secure, and intelligent solution for strengthening cybersecurity resilience in financial and healthcare SAP ecosystems.
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