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Abstract(s)
A indústria de transporte marítimo desempenha um papel crucial no comércio global, atuando como o principal meio de transporte de mercadorias internacionalmente.
A vigilância e monitorização dos espaços marítimos, por parte das entidades com competências nestas áreas pertencentes a Estados costeiros, constitui uma atividade essencial a fim de garantir a segurança das atividades económicas e evitar a ocorrência de atividades ilícitas. O controlo do tráfego marítimo assenta no uso de sistemas de informação sofisticados e no desenvolvimento e exploração de novas tecnologias e de sistemas de vigilância. Estes recursos garantem que as autoridades competentes tenham conhecimento em tempo real sobre as atividades que ocorrem e que ocorreram nos espaços marítimos sob sua jurisdição. No entanto, as fragilidades que estes sistemas apresentam permitem a alguns navios contornar a vigilância constante. Este fenómeno possibilita que atividades ilícitas sejam efetuadas, podendo não serem detetadas pelas autoridades.
Através de algoritmos e procedimentos heurísticos, os dados a serem tratados tem como fonte o sistema Automatic Identification System (AIS). Esta dissertação tem por objetivo desenvolver ferramentas que permitem ao analista detetar situações de ausência de relato de dados AIS e, analisar se os eventos se encontram associados à falta de informação do sistema ou a atividades de natureza ilegal, como Dark Activity.
The maritime transport industry plays a crucial role in global trade, serving as the primary means of transporting goods internationally. ´The surveillance and monitoring of maritime spaces, by costal States entities with competencies in these areas, is an essential activity to ensure the security of economic activities and prevent illicit activities. Maritime traffic control relies on the use of sophisticated information systems and the development and deployment of new technologies and surveillance systems. These resources ensure that the relevant authorities have real-time and historical knowledge of activities occurring within their maritime jurisdictions. However, the vulnerabilities in these systems allow some vessels to evade constant surveillance. This phenomenon enables illicit activities to be carried out, potentially going undetected by the authorities. Through algorithms and heuristic procedures, the data to be processed is sourced from the Automatic Identification System (AIS). The objective of this dissertation is to develop tools that allow analysts to detect instances of AIS data reporting gaps and to analyze whether these events are due to system information deficiencies or are related to illegal activities, such as Dark Activity.
The maritime transport industry plays a crucial role in global trade, serving as the primary means of transporting goods internationally. ´The surveillance and monitoring of maritime spaces, by costal States entities with competencies in these areas, is an essential activity to ensure the security of economic activities and prevent illicit activities. Maritime traffic control relies on the use of sophisticated information systems and the development and deployment of new technologies and surveillance systems. These resources ensure that the relevant authorities have real-time and historical knowledge of activities occurring within their maritime jurisdictions. However, the vulnerabilities in these systems allow some vessels to evade constant surveillance. This phenomenon enables illicit activities to be carried out, potentially going undetected by the authorities. Through algorithms and heuristic procedures, the data to be processed is sourced from the Automatic Identification System (AIS). The objective of this dissertation is to develop tools that allow analysts to detect instances of AIS data reporting gaps and to analyze whether these events are due to system information deficiencies or are related to illegal activities, such as Dark Activity.
Description
Keywords
Vigilância Procedimento Heurístico AIS Dark Activity