Decoding dependencies among the risk factors influencing maritime cybersecurity: lessons learned from historical incidents in the past two decades

Abstract

The distinctive features of maritime infrastructures present significant challenges in terms of security. Disruptions to the normal functioning of any part of maritime transportation can have wide-ranging consequences at both national and international levels, making it an attractive target for malicious attacks. Within this context, the integration of digitalization and technological advancements in seaports, vessels and other maritime elements exposes them to cyber threats. In response to this critical challenge, this paper aims to formulate a novel cybersecurity risk analysis method for ensuring maritime security. This approach is based on a data-driven Bayesian network, utilizing recorded cyber incidents spanning the past two decades. The findings contribute to the identification of highly significant contributing factors, a meticulous examination of their nature, the revelation of their interdependencies, and the estimation of their probabilities of occurrence. Rigorous validation of the developed model ensures its robustness for both diagnostic and prognostic purposes. The implications drawn from this study offer valuable insights for stakeholders and governmental bodies, enhancing their understanding of how to address cyber threats affecting the maritime industry. This knowledge aids in the implementation of necessary preventive measures.

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ORCID for Huanhuan Li: orcid.org/0000-0002-4293-4763

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