Heterogeneous IoT (hetiot) Security: Techniques, Challenges and Open Issues

The HetIoT is a new emergent technology widely used to offer QoS to applications such as health monitoring systems, agriculture 4.0, traffic monitoring, industry 4.0, and civil defense, to name a few. These applications are in high demand as the world is heading towards 6G technology that facilitates a high data transfer rate and faster connectivity. However, technological leaps open the door to invaders, triggering security breaches. Therefore, the article aims to entail security challenges and issues from the HetIoT viewpoint. The conventional approaches need to be revised to handle new trends of security holes and demand advancement in them. As a result, the article systematically reviews the current state-of-the-art traditional techniques, including cryptography, privacy and trust, and access control mechanism. The article exhibits its challenges, open issues, and solution as lightweight protocols and lightweight cryptography concerning traditional approaches. In recent years, a lot of concentration is towards developing intelligent security (IS) mechanisms for HetIoT. Intelligent techniques are data-hungry, and HetIoT emits massive amounts of data, so the use of IS techniques to safeguard the HetIoT is an ideal solution. Therefore, the article also concentrates on IS techniques, including machine learning (ML), deep learning (DL), and deep reinforcement learning (DRL), along with their challenges and open issues. Further, the article details the available benchmarking security-based dataset and experimental tools, platforms, and simulators for the HetIoT. Finally, the review article discusses open research issues and future trends for achieving high security in the HetIoT context.