Abstract: Detecting system anomalies based on log data is important for ensuring the security and reliability of computer systems. Recently, deep learning models have been widely used for log anomaly ...

This project implements an AI-powered log anomaly detection system that analyzes logs stored in Elasticsearch. It uses machine learning to detect unusual patterns and frequencies in log data, with ...

Runs from the command line, accepts log files like /var/log/auth.log, and outputs anomalies in plain text or JSON format.

Abstract: Modern large-scale systems and networks necessitate automated anomaly detection to support the high availability and quality of services. Since logs are an essential data source that can ...

BAW clocks offer low jitter as well as enhanced reliability and performance, enabling safer operation, cleaner data ...

In this study, we applied the anomaly detection method based on sparse structure learning of the element correlation within MD trajectories to identify important features associated with state ...