AIS Transmission Data Quality: Identification of Attack Vectors

Submitted by grigby1 on Fri, 08/28/2020 - 12:02pm

Title	AIS Transmission Data Quality: Identification of Attack Vectors
Publication Type	Conference Paper
Year of Publication	2019
Authors	McFadden, Danny, Lennon, Ruth, O’Raw, John
Conference Name	2019 International Symposium ELMAR
Date Published	Sept. 2019
Publisher	IEEE
ISBN Number	978-1-7281-2181-9
Keywords	AIS, AIS data, AIS networks, artificial intelligence, attack vectors, automatic identification system, Coast Guard, collision avoidance, conceptual countermeasures, data quality, Europe, governments, Human Behavior, legislation, marine communication, marine navigation, maritime sector, obstacle avoidance, potential attack vectors, Protocols, pubcrawl, Receivers, resilience, Resiliency, Scalability, security, security of data, Signal resolution, Standards, state agencies, Timing, transmission data quality, Vectors
Abstract	Due to safety concerns and legislation implemented by various governments, the maritime sector adopted Automatic Identification System (AIS). Whilst governments and state agencies have an increasing reliance on AIS data, the underlying technology can be found to be fundamentally insecure. This study identifies and describes a number of potential attack vectors and suggests conceptual countermeasures to mitigate such attacks. With interception by Navy and Coast Guard as well as marine navigation and obstacle avoidance, the vulnerabilities within AIS call into question the multiple deployed overlapping AIS networks, and what the future holds for the protocol.
URL	https://ieeexplore.ieee.org/document/8918672
DOI	10.1109/ELMAR.2019.8918672
Citation Key	mcfadden_ais_2019

Groups:

Science of Security VO