This research explores how Large Language Models (LLMs) can automate and enhance event log analysis for security professionals, addressing the time-consuming and error-prone nature of manual analysis.

• Automation of repetitive tasks reduces analysis time and human error
• Processing massive volumes of log data more efficiently than traditional methods
• Enhanced detection capabilities for identifying security threats and anomalies
• Reduced resource requirements for security operations teams

For security professionals, this research offers practical pathways to implement AI-assisted log analysis, potentially transforming how organizations detect and respond to security incidents while addressing the growing shortage of cybersecurity talent.

Original Paper: LLM-based event log analysis techniques: A survey