Systematic Cyber Threat Modeling for Maritime Operations: Attack Trees for Shipboard Systems

The increasing reliance on digital and automated systems in the maritime industry has introduced significant cybersecurity risks to ship operations. While prior research has examined cyber risk management, systematic modeling of attack scenarios remains limited. This study addresses this gap by employing attack trees to systematically analyze potential cyberattack pathways against modern ships. Drawing insights from the literature and interviews with 10 experts, this research identifies key vulnerabilities in navigation, operational, and communication systems. The study outlines 20 attack scenarios across three primary objectives: crashing, capsizing, and immobilizing a ship. Expert validation emphasizes the real-world feasibility of these threats, with cyberattack scenarios involving crashing and immobilization deemed the most plausible, while capsizing was considered unlikely due to robust ship designs. The findings highlight the importance of strengthening network security, implementing redundancy measures, and enhancing crew training to mitigate cyber risks.in Expert feedback helped validate these insights, underscoring their relevance to real-world maritime operations. This research presents a systematic threat modeling framework that supports effective risk assessment and cybersecurity strategy development, offering a valuable contribution to the advancement of maritime cybersecurity practices.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-03-24
DOI
https://doi.org/10.3390/jmse13040645
Citations
3
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
9.74
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article

Systematic Cyber Threat Modeling for Maritime Operations: Attack Trees for Shipboard Systems

Omer F. Keskin, Unal Tatar, Hayretdin Bahşi, Karl Lubja
3 citations
Journal of Marine Science and Engineering
Information and Cyber Security
9.74
article

Systematic Cyber Threat Modeling for Maritime Operations: Attack Trees for Shipboard Systems

Omer F. Keskin, Unal Tatar, Hayretdin Bahşi, Karl Lubja
article en
3 citations

Abstract

The increasing reliance on digital and automated systems in the maritime industry has introduced significant cybersecurity risks to ship operations. While prior research has examined cyber risk management, systematic modeling of attack scenarios remains limited. This study addresses this gap by employing attack trees to systematically analyze potential cyberattack pathways against modern ships. Drawing insights from the literature and interviews with 10 experts, this research identifies key vulnerabilities in navigation, operational, and communication systems. The study outlines 20 attack scenarios across three primary objectives: crashing, capsizing, and immobilizing a ship. Expert validation emphasizes the real-world feasibility of these threats, with cyberattack scenarios involving crashing and immobilization deemed the most plausible, while capsizing was considered unlikely due to robust ship designs. The findings highlight the importance of strengthening network security, implementing redundancy measures, and enhancing crew training to mitigate cyber risks.in Expert feedback helped validate these insights, underscoring their relevance to real-world maritime operations. This research presents a systematic threat modeling framework that supports effective risk assessment and cybersecurity strategy development, offering a valuable contribution to the advancement of maritime cybersecurity practices.

Journal of Marine Science and EngineeringVol. 13(4)
Tallinn University of Technology (EE), Albany State University (US), Northern Arizona University (US), University at Albany, State University of New York (US)
Openalex Percentile: Top 3%
Information and Cyber Security
9.74
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Systematic Cyber Threat Modeling for Maritime Operations: Attack Trees for Shipboard Systems — Omer F. Keskin, Unal Tatar, et al. · Journal of Marine Science and Engineering (2025) | TGRS Research Map | TGRS