Analysing Cyber-resiliency of a Marine Navigation System using Behavioural Relations

Abstract

Marine vessels need trustworthy navigation data for safe manoeuvring, but threats exist for external manipulation of signals and on-board systems. This paper employs analysis of behaviours to cross-validate that instruments provide correct information. Deviations from normal behaviour could be effects of malicious cyber-attack or instrument malfunction. Independent of the root cause, faulty information need be disregarded for navigation. This paper shows how instruments’ violation of correct behaviour can be detected and isolated during near-coast navigation. The approach is to analyse topology of information flow and information processing, also referred to as structural analysis. The paper addresses the diagnosis potential for isolation of erroneous information about state of own ship and of surrounding objects. The analysis includes position, ship speed, and heading, which could lead to errors in navigation, to collision or grounding. The paper addresses required sensors, according to the International Maritime Organizations (IMO) Safety of Life at Sea (SOLAS), and also presents potential gains by inclusion of computer vision. Showing that all single and several cases of simultaneous defects are discovered, for own ship and in surroundings, the results demonstrate that resilience of navigation information can be obtained for vessels sailing in coastal waters.

Dimitrios Dagdilelis

ML/AI Engineer

I’m an AI Engineer who loves building intelligent systems that solve real-world problems and push the boundaries of what’s possible. From optimizing processes to creating scalable machine learning models, I thrive at the intersection of data, innovation, and impact.