Centre for maritime cybersecurity

Head of the research group
Keyword
cybersecurity
digitalization of the maritime industry
autonomous ships
Overview
The maritime industry is confronted with major challenges relative to the cybersecurity of the digital systems that are nowadays more and more pervasive in ships, port infrastructure and more globally in the logistic chain. The emergence of autonomous ships, and more largely the wide use of IoT technology in the ship and maritime infrastructures are major topics that warrant specific scrutiny. Addressing these issues need a holistic approach that would encompass the education of seafarers and the human aspect of cybersecurity, the development of a novel technological approach for “security by design”of ships, the operational process, and strategical decision making for all stakeholders. The goal of the Maritime Cybersecurity Centre is to act as a catalyst of the above-mentioned activities.Thanks to EU Horizon 2020 grant (project MariCybERA), this research aims to play important role in Europe-wide expertise development of all dimensions of maritime cybersecurity both in research dimensions, as well in technological development and operational means. For this purpose, the research group is working with professional organisations, industries, government agencies, and academic structures both in Estonia, Europe and worldwide.Specific focuses and competences are as following:‚ Cyber awareness and education of seafarers‚ Trustworthy AI for cybersecurity and autonomous ships‚ Cybersecurity strategy applied to maritime digitalisation ‚ Maritime Security Operation Centre
Important results
Lugo, R. G.; Sütterlin, S.; Knox, B. J.; Bukauskas, L.; Brilingaite, A.; Maennel, O. M. (2023). The human factor in cyber security education. Frontiers in Education, 8, ARTN 1277282−2 pp. DOI: 10.3389/feduc.2023.1277282.
Mirsadeghi, S. M. H.; Bahsi, H.; Vaarandi, R.; Inoubli, W. (2023). Learning From Few Cyber-Attacks: Addressing the Class Imbalance Problem in Machine Learning-Based Intrusion Detection in SoftwareDefined Networking. IEEE Access, 11, 140428−1
Related department
Teadusgrupiga seotud publikatsioonid