Semantic Metadata Annotation for Network Anomaly Detection

This document explains the motivation for defining semantic metadata annotations to help testing, validating and comparing Outlier and Symptom detection systems. These semantic annotations can be supported by supervised and semi-supervised machine learning algorithms and enable data exchange among network operators, vendors and academia, making anomalies apprehensible for humans. The proposed semantics uniforms the network anomaly data exchange between operators and vendors to improve their Service Disruption Detection Systems.