Proactive cybersecurity in industry 4.0: a survey of cybersecurity threat prediction approaches in manufacturing systems

Abstract

This review paper provides a literature review of predictive methods and cybersecurity frameworks essential to safeguard Industry 4.0 manufacturing systems against cyber threats. The review focuses on two key areas: the prediction method and the data used for this prediction. These areas are critical for anticipating cyber threats and implementing effective countermeasures. They underscore the need to combine predictive analytics, proactive threat management, and comprehensive frameworks to safeguard against evolving cyber threats. This review assesses the current state and capability of predictive cybersecurity methods within the manufacturing sector, focusing specifically on their effectiveness in predicting threats. The review also identifies gaps in the current research and suggests directions for future studies to further enhance cybersecurity measures in these vital sectors. The study discusses the main features of each method and highlights promising avenues for future research and applications. This literature review is based on a review of relevant publications from 2010 to February 2025. The analysis reveals significant gaps, particularly in the proactive identification and handling of proactively identifying and handling emerging threats. The review concludes with an analysis of the practical implications of implementing a predictive cybersecurity method and outlines future research directions, underscoring the necessity of adaptive, intelligent cybersecurity solutions to defend the manufacturing industry against cybercrime.