Log-Analysis-for-Anomaly-Detection

The process of log analysis for anomaly detection involves four main steps: log collection, log parsing, feature extraction, and anomaly detection.
To run the whole anomaly detection pipeline follow the below steps:

• create a "log" folder and put the log file in it.
• run "IPLom_parser.py" to parse the log file.
• run "anomaly_detection_benchmark.py" to detect anomalies in the data.
• run "plot_anomaly_detection_charts.py" to plot the charts relative to the metrics of the detection results.

Project report:

• https://davideliu.com/2019/10/26/log-analysis-for-anomaly-detection/

References:

• https://github.com/logpai
• http://jmzhu.logpai.com/pub/slhe_issre2016.pdf