Enhancing Maritime Cybersecurity with Advanced Anomaly Detection using Semi-Markov Processes

The swift evolution of digital technologies in maritime operations has highlighted the critical need for tailored cybersecurity measures, especially to mitigate Distributed Denial of Service (DDoS) attacks targeting essential communication protocols such as NMEA 2000. This study introduces an innovative solution based on stochastic semi-Markov processes, specifically tailored to strengthen the cybersecurity framework of maritime IoT systems. By capturing and analyzing the distinct state transitions within maritime networks, the proposed model effectively identifies abnormal activities and promptly alerts operators to potential DDoS attacks, ensuring robust and uninterrupted maritime communications. Comprehensive simulations demonstrate the model’s superior accuracy, high detection efficiency, and minimal error rates, establishing it as a dependable and specialized approach to protecting critical maritime systems. This research significantly advances maritime cybersecurity by offering proactive and adaptive mechanisms to combat increasingly complex cyber threats.