INTELLIGENT SIEM+ : A CONTEXT-AWARE AND AI-DRIVEN FRAMEWORK FOR ALERT PRIORITIZATION AND AUTOMATED THREAT INSIGHTS IN SECURITY OPERATIONS

Security Information and Event Management (SIEM) systems are central to modern Security Operations Centers (SOCs), yet they continue to suffer from excessive alert volumes, delayed detection, and limited contextual awareness. These challenges lead to analyst fatigue and inefficient incident response. This paper proposes Intelligent SIEM+, a context-aware and AI-driven enhancement framework designed to improve alert prioritization and decision support without replacing existing SIEM deployments. The framework integrates behavioral analysis, anomaly detection, contextual correlation, and natural language summarization to transform raw alerts into actionable security insights. A descriptive survey-based study was conducted among SOC professionals to assess current SIEM limitations and the perceived value of intelligent alert prioritization. The findings indicate strong alignment between operational SOC challenges and the capabilities proposed in Intelligent SIEM+, suggesting that context-aware SIEM enhancements can significantly improve analyst efficiency and situational awareness.