The Industrial Internet of Things (IIoT) refers to the use of the Internet of Things (IoT) in industrial applications. IIoT revolutionizes production and manufacturing by using reliable and secure communication among industrial things with the support of emerging computing technologies. The IIoT encompasses several industrial applications, such as healthcare, robotics, and so on.
Recent researchers are interested in deploying IoT devices to develop industrial applications using automated monitoring, control management, and security maintenance with the support of Fuzzy logic, Heuristic algorithms, Cloud Computing, Artificial Intelligence, and cryptographic algorithms. An increased degree of inter-connectivity improves the IIoT revolution and creates opportunities for cyber-criminals. IoT technologies and applications are still in their infancy.
Researchers face several challenges while applying IoT for industrial use, such as technology, standardization, security, and privacy. Future efforts are in need to solve such challenges and examine the characteristics of different industries to develop adaptive IoT protocols in the industrial environments.
Dynamic monitoring of behavior is an effective way to identify and avoid malicious activities. Generally, Intrusion Detection Systems (IDSs) provide those capabilities. In the IIoT domain, two commonly identified and important requirements for securing IIoT communication are continuous infrastructure monitoring and responding to known and unknown threats.
In IIoT, automatic fault detection is important, and identifying the potential of industrial devices to perform fault detection autonomously. However, it is a challenging topic and needs more attention in the future. Previously, several authors surveyed the security of IIoT. They identify data confidentiality, integrity, privacy, access control, authentication, authorization, and resilience as prominent security requirements for IIoT systems.
Incorporating trusted devices for IIoT communication revolutionizes its production and manufacture. Unguarded industrial things impose communication attacks. Several trust-based security schemes have been designed to identify the attacks which degrade the network performance by modifying the IoT protocols and their features; an accurate and lightweight trust evaluation needs to be considered while applying the IoT protocols to IIoT applications.
The Industrial Internet of Things (IIoT) depends on the collected data from many sensors, controllers, and servers. A part of data processing tasks should be performed at the source rather than in the cloud server. Edge computing is beneficial when it is difficult to connect to a cloud server and when enormous amounts of data are generated frequently.
6TiSCH aims at low-power deterministic IPv6 communication for IIoT networks. It is built on the IEEE 802.15.4 standard for low-rate Wireless Personal Area Network (WPAN), and it can support different categories of devices compared to LPWAN technologies. It is essential to incorporate effective communication protocols and a variety of security properties.
With industrial networks, the number of connected devices or scalability increases rapidly. It makes the IoT protocols face routing and security problems similar to those in IoT applications. It is essential to address many routing performance, scalability, and security issues that need to be addressed in the future. Data confidentiality and privacy issues over resource-constrained IIoT devices need to develop adaptive and lightweight cryptographic algorithms for IIoT applications.
The main challenge for securing IIoT is handling data sets. Due to the large amount of IIoT devices and their traffic, data sets used for machine learning approaches to intrusion detection tend to be preprocessed effectively. Several machine learning algorithms have been designed for IoT. However, it becomes harder to monitor threats when accounting IIoT environment, resource constraints, and application requirements.