Privacy Prevention and Nodes Optimization, Detection of IoUT Based on Artificial Intelligence

Water covers about 71% of the Earth’s surface, which is crucial for transportation, climate regulation, and the production of pharmaceuticals. The Internet of Underwater Things (IoUT) can detect valuable items such as minerals, metals, corals, and coral reefs. One of the crucial purposes is preventing damage from natural disasters. IoT principles helped advance plans for a new underwater network. Underwater networks suffer from some issues, including a lack of dependability, constrained capacity, long propagation delays, high processing requirements, high energy costs, and node detection with encrypted communication. Along with node identification and dynamic network setup, real-time, secure data exchange is one of our main research interests. These problems provide significant challenges for IoUT. Our proposed scheme involves a dynamic graph for network design, an Artificial fish swarm algorithm (AFSA) based on AI for node recognition, and Elliptic Curve Cryptography (ECC) for a secure communication mechanism. For underwater objects, this proposed approach is more trustworthy, safe, and resilient, preventing damage from natural disasters and being helpful for design and secure communication in maritime engineering.