Interpretable Ordinal-aware with Contrastive-enhanced Anomaly Severity Detection on UAV Flight Log Messages

Abstract

This study proposes DroneLog, an interpretable framework for detecting anomalies and the severity levels on drone flight logs, using a multitask learning approach in a unified pipeline. Complying with the multitask learning nature, two target label representations are designed to leverage the shared low-level common features of the input messages over various severity levels.