Proactive Defense Through Retrieval-Augmented Generation for Cloud Security and Continuous Threat Intelligence

Abstract

Cloud computing environments continuously generate large volumes of security telemetry from applications, identities, workloads, containers, networks, endpoints, and infrastructure services. The rapidly changing nature of cyber threats makes conventional security monitoring increasingly dependent on static rules, manually maintained threat intelligence, and fragmented analytical workflows. Retrieval-Augmented Generation (RAG) provides an opportunity to strengthen cloud security by combining large language models with continuously updated external knowledge sources. This research proposes a proactive cloud defense framework that integrates RAG with continuous threat intelligence, cloud telemetry analysis, contextual security reasoning, and automated response support. The proposed framework collects information from threat intelligence feeds, vulnerability databases, security advisories, cloud logs, incident records, configuration repositories, and organizational security knowledge bases. A retrieval layer identifies relevant and current evidence for observed security events, while a generative intelligence layer synthesizes retrieved information to produce contextual threat assessments, attack explanations, risk summaries, and recommended response actions. The methodology incorporates document ingestion, knowledge normalization, semantic indexing, hybrid retrieval, contextual ranking, retrieval-grounded generation, threat correlation, confidence assessment, and continuous feedback. Experimental evaluation can measure retrieval precision, threat-detection accuracy, response latency, false-positive reduction, contextual relevance, and generation faithfulness. The proposed approach aims to reduce knowledge gaps, improve security analyst decision-making, accelerate incident investigation, and enable proactive defense across dynamic cloud infrastructures while maintaining security governance and human oversight.