LogICL: LLM-Driven Anomaly Detection for Cross-Domain Logs

This research explores using Large Language Models (LLMs) to improve cross-domain log anomaly detection. The focus on bridging the semantic gap suggests a valuable contribution to the field of system monitoring and cybersecurity.

• •Leverages LLMs for improved anomaly detection.
• •Addresses the semantic gap in cross-domain log analysis.
• •Potentially benefits system monitoring and security.