Predicting Cybersecurity Threats in Critical Infrastructure for Industry 4.0: A Proactive Approach Based on Attacker Motivations

Abstract

In Industry 4.0, manufacturing and critical systems require high levels of flexibility and resilience for dynamic outcomes. Industrial Control Systems (ICS), specifically Supervisory Control and Data Acquisition (SCADA) systems, are commonly used for operation and control of Critical Infrastructure (CI). However, due to the lack of security controls, standards, and proactive security measures in the design of these systems, they have security risks and vulnerabilities. Therefore, efficient and effective security solutions are needed to secure the conjunction between CI and I4.0 applications. This paper predicts potential cyberattacks and threats against CI systems by considering attacker motivations and using machine learning models. The approach presents a novel cybersecurity prediction technique that forecasts potential attack methods, depending on specific CI and attacker motivations. The proposed model’s accuracy in terms of False Positive Rate (FPR) reached 66% with the trained and test datasets. This proactive approach predicts potential attack methods based on specific CI and attacker motivations, and doubling the trained data sets will improve the accuracy of the proposed model in the future.

Overview of Protocols and Standards for Wireless Sensor Networks in Critical Infrastructures

“…These technologies include industrial automation, robotics, sensors, cyber-physical systems, Industrial Internet of Things (IIoT) [17], big data, block chain, edge computing, digital twin, and artificial intelligence, which are widely considered in manufacturing and service industries [18][19][20][21]. However, the adoption of Industry 4.0 solutions in critical infrastructure also introduces potential risks that need to be carefully addressed, such as cybersecurity and reliability concerns [14,22]. A pivotal aspect of Industry 4.0 is the IIoT.…”

“…Wired communication technologies have played a significant role in industrial monitoring and control networks and have a significant development lead regarding wireless networks. Useful data for understanding the gap between the two technologies can be obtained from the annual research published by HMS Networks [22,23]. HMS Networks conducts an annual assessment of the industrial network market to estimate the distribution of new nodes within factories.…”

Towards a sustainable future: developing a cybersecurity framework for manufacturing

“…Due to poor cyber hygiene, most manufacturers are inviting attackers to access their systems and spread the threat. Cyber hygiene practices include regular data backup, training, privacy shield for screens, permission control, password changes, software updates, access control, penetration tests and VPN use (Borky and Bradley, 2019; Alqudhaibi et al. , 2023).…”

“…Cyber hygiene practices include regular data backup, training, privacy shield for screens, permission control, password changes, software updates, access control, penetration tests, and VPN use (Borky and Bradley, 2019;Alqudhaibi et al, 2023).…”

Company Cybersecurity System: Assessment, Risks and Expectations

“…The green cluster (Appendix A, Figure 1) characterizes the direction of cybersecurity regarding industrial control systems, critical infrastructure, malware and cyberattacks. Industrial control systems used to operate and control the critical infrastructure of enterprises are potential targets of cyber-attacks, so they need appropriate methods, such as machine learning, to predict cyber threats (Alqudhaibi et al, 2023). Cyber incidents can lead to failures of industrial control systems, so Masood et al (2023) suggest using blockchain technologies as tools of the cyber defence system.…”