Logs to the Rescue: Creating meaningful representations from log files for Anomaly Detection

This thesis offers a comprehensive exploration of log-based anomaly detection within the domain of cybersecurity incident response. The research describes a different approach and explores relevant log features for language model training, experimentation with different language models and training methodologies, and the investigation of the...

From log files to train traffic reports : Using Natural Language Generation to explain anomalies from Train Control System log files

The Natural Language Generation field has advanced in generating human readable reports for domain experts in various fields. Nevertheless, Natural Language Generation and anomaly detection techniques have not been used in the rail domain yet. Currently, data analysis and incident reporting for log files from the train control system are...