Cognitive Threat Intelligence for Enterprise Cloud Infrastructure using Contextual Correlation and Automated Response

Abstract

The increasing complexity of enterprise cloud infrastructure has intensified cybersecurity challenges associated with sophisticated attacks, evolving threat patterns, and fragmented security monitoring systems. Traditional security mechanisms frequently depend on predefined rules and isolated alerts, limiting their ability to identify coordinated attacks and respond effectively to emerging threats. This study examines a cognitive threat intelligence framework for enterprise cloud infrastructure using contextual correlation and automated response. The proposed approach integrates artificial intelligence, machine learning, threat intelligence feeds, behavioral analytics, and security information and event management to identify relationships among security events across cloud environments. Contextual correlation combines information about user identities, device behavior, network traffic, application activities, vulnerabilities, and historical incidents to distinguish genuine threats from benign anomalies. Cognitive analysis supports continuous learning from observed events, while automated response mechanisms initiate predefined actions such as session termination, access restriction, endpoint isolation, and suspicious traffic blocking. The research methodology adopts a conceptual framework design and comparative evaluation approach to assess detection accuracy, response latency, false-positive rates, scalability, and operational efficiency. The study also considers challenges related to data quality, explainability, adversarial manipulation, privacy, and integration with existing security infrastructure. The proposed framework aims to improve threat visibility, reduce analyst workload, accelerate incident containment, and strengthen enterprise cloud resilience. Its conceptual contributions provide a foundation for developing adaptive, context-aware cybersecurity systems capable of supporting proactive threat detection and coordinated incident response.