A Cloud and Network Security Framework with ERP Integration: Leveraging AI, Multi-Factor Authentication, Multivariate Classification, and Semantic Precedent Retrieval
DOI:
https://doi.org/10.15662//IJARCST.2021.0404001Keywords:
Cloud security, Network security, ERP integration, Artificial intelligence, Multi-factor authentication, Multivariate classification, Semantic Precedent Retrieval, Anomaly detection, Threat intelligence, Identity management, Cybersecurity automation, , Real-time monitoring, Enterprise security, Adaptive defense, Predictive analyticsAbstract
The integration of artificial intelligence (AI) into cloud and network infrastructures has introduced both opportunities and challenges for enterprise security. This paper proposes a cloud and network security framework with ERP integration that leverages AI to enhance threat detection, access control, and data protection. The framework incorporates multi-factor authentication (MFA) to ensure secure user verification and mitigate unauthorized access across distributed systems. Multivariate classification models are applied to analyze complex network and behavioral datasets, enabling precise identification of anomalies and potential cyber threats. A Semantic Precedent Retrieval module is utilized to reference historical incidents, security policies, and contextual data, supporting intelligent decision-making and automated risk mitigation. Integration with ERP systems ensures centralized governance, seamless data exchange, and consistent enforcement of security policies across enterprise applications. Experimental analysis demonstrates improved threat detection accuracy, reduced false positives, and enhanced operational efficiency. This framework provides a scalable, AI-enabled solution for securing cloud and network environments in modern enterprises.References
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