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Article . 2024 . Peer-reviewed
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Cybersecurity risk assessment of a marine dual-fuel engine on inland waterways ship

Authors: Victor Bolbot; La Xiang; Päivi Brunou; Mikko Kiviharju; Yu Ding; Osiris Valdez Banda;

Cybersecurity risk assessment of a marine dual-fuel engine on inland waterways ship

Abstract

Increased connectivity renders the ships more cost-effective but also vulnerable to cyberattacks. Since ships are assets of significant value and importance, they constitute a lucrative object for cyber-attacks. The power and propulsion functions are among the most safety critical and essential for ship operations. Simultaneously, the use of Dual-Fuel (DF) engines for power generation and propulsion has become very popular in the recent years. The aim of this research is the risk identification and analysis of potential cybersecurity attack scenarios in a DF engine on inland waterways ship. For this purpose, we employ an adapted version of Failure Modes, Vulnerabilities and Effects Analysis (FMVEA). In our approach we demonstrate how the implementation of FMVEA can be interconnected with the existing assurance processes for maritime engines and novel developments in the field of risk theory. We also provide insights in the riskiest cybersecurity attacks on DF engine and how to reduce their risks.

Country
Finland
Keywords

vulnerabilities and effects analysis, cybersecurity, inland waterways ship, risk assessment, maritime regulations, failure modes, Dual fuel engine

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green