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Article

AIS Data Vulnerability Indicated by a Spoofing Case-Study

1
Faculty of Maritime Studies and Transport, University of Ljubljana, 6320 Portorož, Slovenia
2
Faculty of Maritime Studies, University of Split, 21000 Split, Croatia
3
Croatian Defence Academy, University of Split, 21000 Split, Croatia
*
Author to whom correspondence should be addressed.
Academic Editor: Cezary Specht
Appl. Sci. 2021, 11(11), 5015; https://doi.org/10.3390/app11115015
Received: 26 April 2021 / Revised: 17 May 2021 / Accepted: 25 May 2021 / Published: 28 May 2021
This paper takes a close look at the landscape of the Automatic Identification System (AIS) as a major source of information for maritime situational awareness (MSA) and identifies its vulnerabilities and challenges for safe navigation and shipping. As an important subset of cyber threats affecting many maritime systems, the AIS is subject to problems of tampering and reliability; indeed, the messages received may be inadvertently false, jammed, or intentionally spoofed. A systematic literature review was conducted for this article, complemented by a case study of a specific spoofing event near Elba in December 2019, which confirmed that the typical maritime AIS could be easily spoofed and generate erroneous position information. This intentional spoofing has affected navigation in international waters and passage through territorial waters. The maritime industry is neither immune to cyberattacks nor fully prepared for the risks associated with the use of modern digital systems. Maintaining seaworthiness in the face of the impact of digital technologies requires a robust cybersecurity framework. View Full-Text
Keywords: Automatic Identification System (AIS); cybersecurity; anomaly detection; spoofing; maritime situational awareness; the safety of navigation Automatic Identification System (AIS); cybersecurity; anomaly detection; spoofing; maritime situational awareness; the safety of navigation
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MDPI and ACS Style

Androjna, A.; Perkovič, M.; Pavic, I.; Mišković, J. AIS Data Vulnerability Indicated by a Spoofing Case-Study. Appl. Sci. 2021, 11, 5015. https://doi.org/10.3390/app11115015

AMA Style

Androjna A, Perkovič M, Pavic I, Mišković J. AIS Data Vulnerability Indicated by a Spoofing Case-Study. Applied Sciences. 2021; 11(11):5015. https://doi.org/10.3390/app11115015

Chicago/Turabian Style

Androjna, Andrej, Marko Perkovič, Ivica Pavic, and Jakša Mišković. 2021. "AIS Data Vulnerability Indicated by a Spoofing Case-Study" Applied Sciences 11, no. 11: 5015. https://doi.org/10.3390/app11115015

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