Improvement of ship operator reliability for potential cyber-attack on integrated navigation system (INS) at ship bridge

Since ships become increasingly reliant on integrated navigation systems (INS), cyber-attack risk targeting the systems poses significant threats to safety and operational efficiency. This paper presents a comprehensive research aimed at improving the reliability of ship operators in managing potential cyber-attacks on ship navigation systems. To achieve this purpose, a robust integrated risk analysis modelling is used by adopting the Bayesian belief network (BBN) and evidential reasoning (ER) under the cognitive reliability and error analysis method (CREAM) approach. The article assesses the reliability of bridge watchkeeping officers during a GPS spoofing attack on a ship during coastal navigation. In the model, BBN is capable of determining the probability distribution of Contextual Control Modes in CREAM, as the ER copes with the uncertainty and subjectivity of expert judgments. Accordingly, the paper explores the vulnerabilities within INS operations and identifies key factors that influence operator performance under attack scenarios. The finding of the research shows that the human reliability for GPS spoofing attacks on INS at ship bridge is 9.74E−01 which refers ‘strategic’ control mode. The results provide valuable insights into reducing human error and strengthening the overall reliability against cyber-attacks for ships.