AI-Driven Security Intelligence and Real-Time Telemetry Analytics for Cloud-Native Threat Detection and Response
DOI:
https://doi.org/10.15662/IJARCST.2024.0706041Keywords:
cloud-native security, security telemetry, artificial intelligence, threat intelligence, real-time analytics, anomaly detection, Kubernetes security, machine learning, SIEM, cybersecurityAbstract
Cloud-native computing has transformed enterprise information systems by enabling highly scalable, distributed, containerized, and dynamically managed applications. However, the rapid generation of security telemetry from containers, Kubernetes clusters, microservices, APIs, cloud workloads, identity systems, and network infrastructure creates significant challenges for conventional security monitoring approaches. This paper proposes a cloud-native security telemetry processing framework that integrates artificial intelligence (AI)-based threat intelligence with real-time security analytics to improve threat detection, correlation, prioritization, and response. The proposed approach collects heterogeneous telemetry from cloud infrastructure and applications, normalizes and enriches security events, and applies machine-learning techniques to identify anomalous behavior and potential attacks. Threat intelligence is incorporated through contextual indicators, behavioral patterns, vulnerability information, and reputation data to enhance analytical accuracy. A streaming analytics layer processes telemetry continuously using scalable event-processing mechanisms, while AI models support anomaly detection, classification, risk scoring, and attack-pattern identification. The methodology also introduces feedback mechanisms through which analyst decisions and incident outcomes can improve subsequent detection. The proposed framework aims to reduce detection latency, false positives, and analyst workload while improving visibility across dynamic cloud environments. By combining telemetry engineering, threat intelligence, and real-time AI analytics, the approach provides a flexible foundation for proactive and adaptive cloud-native security operations
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