Identifying and Predicting Cybersecurity Threats in Industry 4.0 Based on the Motivations Towards a Critical Infrastructure

Abstract

Industry 4.0 (I4.0) is an emerging concept describing the business setting application of a broad set of digitalisation technologies, connectivity, and automation. The most common critical infrastructure (CI) uses Industrial Control Systems (ICS) for operation and supervisory control. However, the Supervisory Control and Data Acquisition (SCADA) and Internet of things (IoT) systems are examples of ICSs applications. These systems, like any other systems exposed to many security risks and are vulnerable to many threats. This is mainly due to the lack of objective standards and proactive security countermeasures that companies unintentionally neglected in the early stages of designing these systems. It is also due to the absence of managerial and technical skills necessary to implement them. Therefore, identifying and preventing potential security threats against CIs is the focus of this paper. A novel security approach concept that can predict cybersecurity threats based on the CI nature and take into consideration the attack motivations accordingly has been delivered in this paper. The proposed concept of this approach will also facilitate the detection of potential attack types and the required countermeasures in particular infrastructures.