Comparative Analysis of Deep Learning Models for Intrusion Detection System in UIoT

The Internet of Underwater Things (UIOT) is a new technology ecosystem that is being developed for the purpose of linking things in marine and underwater environments. IoUT technologies are made possible by a significant number of sensors and actuators that have been deployed. When viewed from a scientific point of view, these pervasive sensing devices are considered to be tools for data collection. These tools have the potential to be enhanced with artificial intelligence and big data analytics, which may be used for automated monitoring as well as prospective research. In this research, introduction to UIOT, UIOT Architecture and their security goals are discussed. Then the concept of integration of deep learning and UIOT are explained. Then, an extensive review of the Internet of Things and marine data analytics are conducted in order to solve many research gaps. Additionally, comparative analyses of existing methods are done. Finally, the future works for intrusion detection system for UIOT are listed.