From Sustainable Process Integration to Intelligent Cyber Defense Using AI-Driven Cloud Platforms for Secure and Scalable Enterprise Systems
DOI:
https://doi.org/10.15662/IJARCST.2023.0603008Keywords:
AI-Driven Security, Cyber Defense, Cloud Platforms, Predictive Analytics, Scalable Enterprise Applications, Threat Detection, Anomaly DetectionAbstract
As enterprises increasingly migrate to cloud-based infrastructures, traditional physical security measures are insufficient to protect against sophisticated cyber threats. Modern enterprise systems require intelligent cyber defense mechanisms that integrate predictive analytics, AI-driven threat detection, and scalable cloud-native architectures. This paper proposes an AI-driven cyber defense framework leveraging cloud platforms to provide secure, predictive, and scalable protection for enterprise applications. The framework combines continuous monitoring, machine learning-based anomaly detection, threat intelligence integration, and automated incident response. AI algorithms analyze network traffic, system logs, and user behavior to predict potential threats, enabling proactive defense measures. Cloud-native architecture ensures elasticity and rapid deployment of security modules while maintaining operational efficiency. Experimental evaluation demonstrates improved threat detection accuracy, reduced response times, and enhanced system resilience against simulated attacks. The framework also integrates security compliance and auditing mechanisms to meet industry regulations such as ISO 27001, HIPAA, and GDPR. By transitioning from traditional physical protection to AI-driven cyber defense, enterprises can enhance security posture, reduce operational risks, and maintain service continuity. The study contributes a unified approach for intelligent, predictive, and scalable cybersecurity in modern enterprise applications.
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