Behavior Analysis Modulus for harbor security

This paper focuses on protecting harbor by monitoring the behavior of ships moving in the harbor. In particular, we propose to combine a probabilistic Hidden Markov Model approach with a formal language approach to model and recognize usual and unusual ship behavior. The probabilistic approach was mainly used to recognize usual ship behavior. However, the reactive approach was used to recognize abnormal ship behavior and classify it into aggressive and transgressive. By combining probabilistic and reactive approaches, we conceived a Behavior Analysis Modulus that we called BAM. It is a decision support system for port team security that aims to generate security advice on ships as they enter into the harbor.