Uncovering Hidden Concepts from AIS Data: A Network Abstraction of Maritime Traffic for Anomaly Detection

The compulsory use of Automatic Identification System (AIS) for many vessel types, which has been enforced by naval regulations, has opened new opportunities for maritime surveillance. AIS transponders are rich sources of information that everyone can collect using an RF receiver and provide real-time information about vessels' position. Properly taking advantage of AIS data, can uncover potential illegal behavior, offer real-time alerts and notify the authorities for any kind of anomalous vessel behavior. In this article, we extend an existing network abstraction of maritime traffic, that is based on nodes (called way-points) that correspond to naval areas of long stays or major turns for vessels (e.g. ports, capes, offshore platforms etc.) and edges (called traversals) that correspond to the routes followed by vessels between two consecutive way-points. The current work, focuses on the connections of this network abstraction and enriches them with semantic information about the different ways that vessels employ when traversing an edge. For achieving this, it proposes an alternative of the popular density based clustering algorithm DB-Scan, which modifies the proximity parameter (i.e. epsilon) of the algorithm. The proposed alternative employs in tandem the difference in (i) speed, (ii) course and (iii) position for defining the distance between two consecutive vessel positions (two consecutive AIS signals received from the same vessel). The results show that this combination performs significantly better than using only the spatial distance and, more importantly, results in clusters that have very interesting properties. The enriched network model can be processed and further examined with data mining techniques, even in an unsupervised manner, in order to identify anomalies in vessels' trajectories. Experimental results on a real dataset show the network's potential for detecting trajectory outliers and uncovering deviations on a vessel's route.