No 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) [20], 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.

No abstract

Cyber-resilience is an increasing concern in developing autonomous navigation solutions for marine vessels. This paper scrutinizes cyber-resilience properties of marine navigation through a prism with three edges: multiple sensor information fusion, diagnosis of not-normal behaviours, and change detection. It proposes a two-stage estimator for diagnosis and mitigation of sensor signals used for coastal navigation. Developing a Likelihood Field approach, a first stage extracts shoreline features from radar and matches them to the electronic navigation chart. A second stage associates buoy and beacon features from the radar with chart information. Using real data logged at sea tests combined with simulated spoofing, the paper verifies the ability to timely diagnose and isolate an attempt to compromise position measurements. A new approach is suggested for high level processing of received data to evaluate their consistency, that is agnostic to the underlying technology of the individual sensory input. A combined parametric Gaussian modelling and Kernel Density Estimation is suggested and compared with a generalized likelihood ratio change detector that uses sliding windows. The paper shows how deviations from nominal behaviour and isolation of the components is possible when under attack or when defects in sensors occur.