Optimized Routing and Security in Maritime Safety Applications

In recent years, globalization has made shipping is a vital part of the world economy. Additionally, hackers are now aware of the flaws in these maritime vessel systems. Users frequently struggle to find the necessary comprehensive navigational information. As a result, managing and protecting maritime vessel networks from cyber-attacks is crucial. The purpose of this work is to monitor the ship and gives operational performance of speed log, thrust, rudder angle, position, and direction, which are sensed with the aid of sensors mounted to the ship. The data, which is obtained by the sensor are collected and sent to the Internet of things (IoT). After receiving the data, IoT transfer the information to the cloud. Genetic algorithm-based ANN classifier (GA-ANN) is used in this work to identify the shortest path of data transmission. A 64-bit Two Fish Algorithm based on key management is adopted for safety concerns, providing better data protection during transfer. As a result, the information is effectively transported to the cloud, with benefits including increased throughput, the best route, reduced energy use, and latency is achieved by using the proposed GA-ANN classifier.