A Review of Intelligent Intrusion Detection System for Heterogeneous Internet of Things (HeIoT): Mitigation Attacks, Techniques, Deployment Strategy, and Challenges

Abstract

A new area of study called heterogeneous internet of things (HetIoT) has the potential to significantly alter both how we currently understand basic computer science concepts and how we live in the future. HetIoT is being used in an expanding variety of fields, including advanced manufacturing, smart manufacturing, smart cities, intelligent transportation, environmental monitoring, and security systems. HetIoT will thus enrich our lives and offer a variety of useful services in the future by relying on strong application fields. In this review paper, we give an overview of intelligent IDS for HeIoT and talk about the key elements of its design, such as the sensing layers, networking layers, cloud architecture, and HeIoT architectural applications. We cover the present research on intelligent IDS for HeIoT and talk about the many methods used by researchers, including deep reinforcement learning, deep learning, supervised learning, unsupervised learning, and reinforcement learning. We also look at the difficulties in installing IDS for HeIoT, such as resource limitations, scalability, and heterogeneity, and we investigate unresolved issues and knowledge gaps in this area. The contributions of this study provide insights into the creation of intelligent IDS for HeIoT, highlighting the difficulties and unsolved issues in this area, and offering suggestions for future research.