AI-Enabled Machine Learning Solutions for Cybersecurity and Web Analytics in Enterprise Healthcare Systems with SAP

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Published: 2025-12-15
DOI: https://doi.org/10.15662/IJRPETM.2025.0806023
Keywords:
AI, Machine Learning, Cybersecurity, Web Analytics, Enterprise Healthcare Systems, Big Data, SAP

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Vinícius Gabriel Lopes
Independent Researcher, Brazil

Abstract

The increasing digitization of enterprise healthcare systems has heightened the need for advanced cybersecurity and intelligent web analytics to protect sensitive data and ensure operational resilience. This study presents an AI-enabled machine learning framework designed to enhance cybersecurity and web analytics in enterprise healthcare environments using SAP platforms. The proposed approach leverages big data analytics and machine learning models to detect cyber threats, identify anomalies, and analyze web traffic patterns in real time. By integrating AI-driven security mechanisms with SAP-based enterprise systems, the framework enables proactive threat detection, risk mitigation, and improved system visibility. Privacy-aware controls, access management, and data governance mechanisms are incorporated to safeguard patient information and maintain regulatory compliance. Experimental analysis demonstrates improved detection accuracy, scalability, and performance, making the proposed solution suitable for large-scale, cloud-enabled healthcare enterprises.

Article Details

Issue

Vol. 8 No. 6 (2025): International Journal of Research Publications in Engineering, Technology and Management

Section

Articles

How to Cite

AI-Enabled Machine Learning Solutions for Cybersecurity and Web Analytics in Enterprise Healthcare Systems with SAP. (2025). International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(6), 13194-13201. https://doi.org/10.15662/IJRPETM.2025.0806023

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