A review on the static and dynamic risk assessment methods for OT cybersecurity in industry 4.0

Abstract

The inherent vulnerabilities of Operational Technology (OT) systems to cyberattacks have historically been mitigated through the practice of air-gapping, effectively isolating them from broader industrial networks and thereby maintaining a level of security. However, the beginning of the fourth industrial revolution (Industry 4.0) signs a concept shift towards increased interconnectivity, enhanced visibility, and digital continuity. The transition towards Industry 4.0 has been characterized by a marked increase in security breaches within industrial settings, leading to a variety of hazardous outcomes. These incidents underscore the importance of cybersecurity within OT environments, necessitating the development and implementation of strict cybersecurity measures to safeguard against potential threats. In response to this emerging threat landscape, there has been a notable shift from static risk assessment methodologies towards more dynamic approaches, particularly with the incorporation of Artificial Intelligence (AI) technologies. This paper presents a comprehensive literature review that explores various risk assessment approaches within the context of Industry 4.0, focusing on industrial systems. It outlines the transition from traditional, static risk assessment methods to innovative, dynamic risk assessment strategies facilitated by the integration of AI.