Abstract
Industrial Internet of Things (IIoTs) are the extensions of the Internet of Things (IoTs) and have paved the way towards the industry revolution 4.0. IIoT accelerates the industry automation of internal and external working process including transport, manufacturing, and marketing units with a number of connected devices. Being the extension of IoT, it inherits the insecurities of the technology; however, this sensor-configured infrastructure of IIoT needs some extra effort to customize the existing security solutions. In spite of the reconstructions of security models, the scope of improved developments is open to detect unknown attacks. The present study helps the researchers to understand the cause for intrusion by classifying and comparing various attacks of each IIoT layers. The main focus of this survey is to analyze various security issues faced by IIoT and provide a comparative analysis on the available solutions to enhance the industrial IoTs’ protection systems. This study also notifies some open research problems for academia, technologists, and researchers to flourish the IIoT domain and its security aspects.
Highlights
Internet-of-Thing (IoT) has created the changeover from the digital world to a smart connected world by establishing an end-to-end communication with automated services and minimizing human intervention
2) We show a taxonomy of solutions against security issues in Industrial Internet of Things (IIoTs) including the approaches of machine learning, deep learning and other techniques
Considering security violation as the main issue of the study, we have focused on existing surveys related to security and intrusion detection to reach the current advancement of the research area in Industry Internet of Things (IoTs)
Summary
Internet-of-Thing (IoT) has created the changeover from the digital world to a smart connected world by establishing an end-to-end communication with automated services and minimizing human intervention. SECURITY FRAMEWORKS FOR IIoT Industrial Control System (ICS) is a centralized control scheme to operate, manage, monitor and control the complete industrial process It is an integrated component comprised of sensors, physical devices, controllers and complex networks for communication. Various frameworks and models are proposed for device level, network level, and database-level detection for IIoTs. In the following subsections we have discussed these solutions based on used machine learning, deep learning and other techniques. High computational cost and limited to resource-constrained devices are the major falloffs of this technique [50]
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