Log2graphs: An Unsupervised Framework for Log Anomaly Detection with Efficient Feature Extraction

Understand

In the era of rapid Internet development, log data has become indispensable for recording the operations of computer devices and software.

• These data provide valuable insights into system behavior and necessitate thorough analysis.
• Recent advances in text analysis have enabled deep learning to achieve significant breakthroughs in log anomaly detection.
• However, the high cost of manual annotation and the dynamic nature of usage scenarios present major challenges to effective log analysis.