Live log analysis using integrated SIEM and IDS using Machine Learning

Abstract

Live log analysis using integrated SIEM and IDS using Machine Learning Abstract: The integration of Security Information and Event Management (SIEM) systems and Intrusion Detection Systems (IDS), augmented by machine learning methodologies, to facilitate real-time log analysis for proactive threat identification and response. Through a comprehensive analysis, it delineated the architectural framework, data aggregation mechanisms, and correlation methodologies inherent in this integrated approach. Furthermore, the paper elucidates the pivotal role of machine learning algorithms, particularly in anomaly detection and predictive analytics, in enhancing the efficiency of threat detection within this context. This research underscores the imperative of leveraging integrated SIEM and IDS systems empowered by machine learning capabilities to fortify organizational cybersecurity defenses and adeptly navigate the complexities of contemporary threat landscapes.