In this study, we propose a real-time ship anomaly detection method driven by Automatic Identification System (AIS) data. The method uses ship trajectory clustering classes as a normal model and a deep learning algorithm as an anomaly detection tool. The method is divided into three main steps: (1) quality maintenance of the original AIS data, (2) extraction of normal ship trajectory clusters using Density-Based Spatial Cluste...