Efficient Isolation Forest for Anomaly Detection in System Logs using Behavioral Feature Fusion
Detecting anomalies in system logs looks straightforward from the outside, yet logs are voluminous, the signalto-noise ratio is low, and standard Isolation Forest (IF) scores each entry in isolation, with no sense of whose entry it is; a user repeating one command in a loop stays invisible to it. This work addresses th...