AI-Powered Cybersecurity and Predictive Vulnerability Intelligence for SAP-Enabled Next-Generation Cloud Infrastructure

Arun Baidya; Arun Baidya

doi:10.15662/IJAESIT.2023.0606005

Articles

AI-Powered Cybersecurity and Predictive Vulnerability Intelligence for SAP-Enabled Next-Generation Cloud Infrastructure

Arun Baidya

Data Architect, EY (AI &Data), New Jersey, United States

Abstract

Modern enterprise infrastructures increasingly rely on cloud-native platforms integrated with SAP enterprise systems to support critical business operations such as financial management, logistics coordination, supply chain optimization, and enterprise analytics. While cloud infrastructures offer scalability, flexibility, and operational efficiency, they also introduce new cybersecurity challenges due to the complexity of distributed architectures, dynamic resource provisioning, and interconnected enterprise applications. Traditional cybersecurity approaches that rely primarily on rule-based detection mechanisms often struggle to identify sophisticated cyber threats and emerging vulnerabilities in highly dynamic cloud environments.

Artificial intelligence (AI) has emerged as a powerful technology for enhancing enterprise cybersecurity by enabling predictive threat detection, automated anomaly analysis, and intelligent vulnerability management. AI-driven cybersecurity frameworks leverage machine learning algorithms to analyze large volumes of enterprise system data, identify suspicious behavioral patterns, and proactively detect potential security threats before they escalate into major incidents.

This research proposes an AI-powered cybersecurity and predictive vulnerability intelligence framework designed specifically for SAP-enabled next-generation cloud infrastructure. The framework integrates machine learning–based anomaly detection models with enterprise governance mechanisms and real-time security monitoring systems. The proposed architecture continuously analyzes enterprise operational data generated from SAP applications, cloud infrastructure logs, network activity records, and identity access management systems.

Experimental evaluation demonstrates that the proposed AI-driven framework significantly improves enterprise threat detection accuracy, reduces incident response time, and enhances predictive vulnerability identification within complex cloud environments. The results confirm that AI-powered cybersecurity architectures can play a critical role in strengthening the resilience and security posture of modern enterprise infrastructures.

Article Information

Journal	International Journal of Advanced Engineering Science and Information Technology (IJAESIT)
Volume (Issue)	Vol. 6 No. 6 (2023): International Journal of Advanced Engineering Science and Information Technology (IJAESIT)
DOI	https://doi.org/10.15662/IJAESIT.2023.0606005
Pages	12863-12870
Published	December 21, 2023
Copyright	Creative Commons Attribution 4.0 International License
Open Access	This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite	Arun Baidya (2023). AI-Powered Cybersecurity and Predictive Vulnerability Intelligence for SAP-Enabled Next-Generation Cloud Infrastructure. International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , Vol. 6 No. 6 (2023): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , pp. 12863-12870. https://doi.org/10.15662/IJAESIT.2023.0606005

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