Web Log Anomaly Detection Based on Isolated Forest Algorithm

摘要

In order to improve the detection rate and time efficiency of the web log based anomaly detection method, a web log anomaly detection method based on the isolated forest algorithm is proposed. By analyzing the web log anomalies, an anomaly detection framework based on web logs was constructed, the web features for anomaly detection are extracted, a mathematical model is built for the web log and the feature values are calculated, and an anomaly detection is performed using the isolated forest. Compared with other methods through experiments, the results show that the method has greatly improved detection accuracy and detection efficiency.