AI-Driven Privacy and Zero-Trust Architectures in ERP: Real-Time Cybersecurity Automation for Oracle-Based Enterprises
DOI:
https://doi.org/10.15662/IJARCST.2024.0703004Keywords:
AI-driven cybersecurity, zero-trust architecture, ERP security, real-time threat detection, privacy-preserving mechanisms, Oracle ERP, automated access control, behavioral analytics, enterprise resilience, adaptive securityAbstract
Enterprise Resource Planning (ERP) systems are critical to modern business operations, yet their centralized nature makes them prime targets for cyber threats. This paper proposes an AI-driven framework that integrates privacy-preserving mechanisms with zero-trust architectures to enable real-time cybersecurity automation in Oracle-based ERP environments. Leveraging machine learning and behavioral analytics, the framework continuously monitors system activity, detects anomalies, and enforces adaptive access controls without disrupting operational workflows. By combining AI capabilities with zero-trust principles, the approach ensures granular authorization, data confidentiality, and resilience against advanced cyber threats. A case-based evaluation highlights improved threat detection accuracy, rapid response times, and strengthened privacy compliance, demonstrating the framework’s potential for safeguarding enterprise ERP systems while maintaining business continuity in dynamic digital environments.
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