Maritime Anomaly Detection of Malicious Data Spoofing and Stealth Deviations from Nominal Route Exploiting Heterogeneous Sources of Information
Enrica d’Afflisio, Paolo Braca, Luigi Chisci, Giorgio Battistelli, Peter Willett · 2021 IEEE 24th International Conference on Information Fusion (FUSION) · 2021
Based on a proper stochastic formulation of the vessel dynamic, exploiting piecewise Ornstein-Uhlenbeck (OU) mean-reverting processes, we propose an effective anomaly detection procedure to jointly reveal Automatic Identification System (AIS) data spoofing and/or surreptitious deviations from the planned route. Supported by reliable information from monitoring systems (coastal radars and spaceborne satellite sensors), an expanded five-hypothesis testing problem is posed involving two anomaly detection strategies based on the Generalized Likelihood Ratio Test (GLRT) and the Model Order Selection (MOS) methodologies.