Exploring Security and Data Privacy Issues in Industrial Internet of Things (IIoT)—A Review

Technology has profoundly impacted people's daily lives, privacy, and security with the exponential increase in the number of devices connected to the Internet. The Industrial Sector has therefore found its interest in the Internet of Things (IoT) in the development of smart devices, leading to the creation of the “Industrial Internet of Things (IIoT).” In recent years, data analytics and automation have improved the quality of products end users use, allowing adversaries to discover new security or privacy vulnerabilities. This research aims to provide a broader overview of the IIoT technology, its components, and its applications. Furthermore, the research comprehensively studies the recent literature published on security and privacy issues across IIoT. Additionally, the research provides desirable contributions by analyzing such issues and providing recommendations on safeguarding IIoT assets, data, and human resources. Finally, this research covers some studies of various Machine Learning (ML), Deep Learning (DL), and Neural Networks (NN) models to develop an Intrusion Detection System (IDS) for the IIoT space. It identifies open research areas in the current IIoT space and newer technologies such as Blockchain, Software Defined Networks (SDN), and Zero Trust (ZT), which can be helpful to academicians and researchers in exploring the security and privacy issues of IIoT.