Cyber security risk assessment of navigation sensors in maritime autonomous surface ships

Abstract

This thesis conducts a risk assessment for key maritime autonomous surface ships (MASS) navigation technologies using the Formal Safety Assessment (FSA) framework. MASS is in the early stages, and understanding risks is crucial to ensuring safe and reliable autonomous operations. Risks are assessed in the context of global autonomous operations with MASS levels 3 and 4, which represent a high level of autonomy. Risks are identified from the literature and an expert interview with an academic researcher is used to validate the findings. Mitigation solutions are also covered for identified risks. The assessment focuses on six core navigation technologies: Global Navigation Satellite System (GNSS), Automatic Identification System (AIS), radar, LiDAR, and Electronic Chart Display and Information System (ECDIS) and Inertial Measurement Unit (IMU). Common vulnerabilities in these technologies include spoofing and jamming. The assessment suggests that attacks on a single key technology are relatively easy and inexpensive to implement, but effectively disabling the navigation system requires simultaneous attacks on multiple key technologies. The thesis integrates the current findings on risks and mitigation strategies for MASS, offering a structured basis for future research.