Paper Type
Complete
Paper Number
PACIS2026-1105
Description
This paper examines cybersecurity vulnerabilities and defense mechanisms of the Automatic Identification System (AIS) from an information systems perspective. AIS, as a core component of maritime cyber–physical infrastructure, plays a critical role in situational awareness and decision support, yet remains inherently vulnerable due to its open, unauthenticated design. The study classifies key vulnerabilities affecting data integrity, availability, and authenticity, and analyzes threat scenarios such as spoofing, ghost vessels, and traffic manipulation. It highlights how compromised AIS data propagate through interconnected maritime information systems, degrading information quality and decision-making reliability. To address these challenges, the paper proposes a layered defense approach integrating technical safeguards, AI-based anomaly detection, and organizational measures. By reframing AIS cybersecurity as an information systems problem, the study contributes a holistic framework linking vulnerabilities, information quality, and resilience, supporting the development of more secure and trustworthy maritime information infrastructures.
Recommended Citation
Neumann, Tomasz, "Cybersecurity Vulnerabilities and Defense Mechanisms in the Automatic Identification System (AIS): An Information Systems Perspective" (2026). PACIS 2026 Proceedings. 2.
https://aisel.aisnet.org/pacis2026/dig_sec/dig_sec/2
Cybersecurity Vulnerabilities and Defense Mechanisms in the Automatic Identification System (AIS): An Information Systems Perspective
This paper examines cybersecurity vulnerabilities and defense mechanisms of the Automatic Identification System (AIS) from an information systems perspective. AIS, as a core component of maritime cyber–physical infrastructure, plays a critical role in situational awareness and decision support, yet remains inherently vulnerable due to its open, unauthenticated design. The study classifies key vulnerabilities affecting data integrity, availability, and authenticity, and analyzes threat scenarios such as spoofing, ghost vessels, and traffic manipulation. It highlights how compromised AIS data propagate through interconnected maritime information systems, degrading information quality and decision-making reliability. To address these challenges, the paper proposes a layered defense approach integrating technical safeguards, AI-based anomaly detection, and organizational measures. By reframing AIS cybersecurity as an information systems problem, the study contributes a holistic framework linking vulnerabilities, information quality, and resilience, supporting the development of more secure and trustworthy maritime information infrastructures.
Comments
08-Security