## 1 Introduction
The vessel movement data recording systems introduced in the Baltic Sea and other maritime areas allow for subsequent or ongoing analysis. Records from the automatic identification system, AIS, are used. In this system, each conventional (but not only conventional) vessel regularly transmits static data such as vessel identification, size, draught, type, and destination, and, with varying frequency depending on speed, dynamic data such as current position, course, speed, and rate of turn [1]. The authors propose a method adapted from medical screening procedures for use by coastal state authorities, enabling coordinated action based on radio-electronic surveillance of both national and adjacent waters. This approach is combined with a multi-criteria decision analysis (MCDA) of vessel behavior, enhanced by continuous analysis of available government and commercial databases that record vessel status and behavioral history. The method is based on comparing vessels with one another. Against the background of ships exhibiting positive characteristics, operating in accordance with regulations, and having a clean record, suspicious vessels will stand out in the final evaluation. In order to identify the groups and individual criteria, a survey (expert study) was conducted among participants of courses for the Master Mariner license and management-level deck department courses at the Officer Training Center of the Maritime University of Szczecin, as well as members of the Maritime Experts Association (MEA) in Szczecin. This study included participants from four such courses. A total of 75 questionnaires were collected, addressing, among other things, which groups of criteria and individual criteria were considered necessary, along with their assigned weights. The authors developed a list of evaluation criteria and designed a procedure for a vessel selection system. Computational experiments were carried out, leading to the formulation of a set of recommendations for the early detection of suspicious vessels. The proposed method will enable the early identification of potentially dangerous vessels for further close monitoring. The initial classification of a vessel as suspicious does not constitute evidence of criminal activity but rather serves as a trigger for further coordinated action. Applying this method will allow for an immediate yet proportionate response to potentially suspicious vessel behavior, ultimately helping to prevent damage or destruction of strategic infrastructure. In the literature, trajectory prediction based on AIS data is the most commonly addressed approach. In contrast, we propose an initial rapid pre-selection using MCDA, followed by trajectory prediction only when necessary. This reduces the burden on tracking systems and computational resources associated with predicting the movement of dozens or even hundreds of vessels. This paper is divided into several sections. The literature background and review of related publications are presented in the State of the Art Section. Section 2 presents a block diagram of the developed system along with its explanation, the AIS data decoding procedure, the computational principles of the PROMETHEE method, and a description of the criteria family and the set of alternatives. Section 3 includes computational experiments and provides graphical outputs along with their interpretation. In Section 4, the limitations and potential of the proposed method are addressed. A summary of this study is provided in Section 5.