Abstract:
This paper provides the complete details of current challenges and solutions in
the cybersecurity of cyber-physical systems (CPS) within the context of the IIoT and its
integration with edge computing (IIoT–edge computing). We systematically collected and
analyzed the relevant literature from the past five years, applying a rigorous methodology
to identify key sources. Our study highlights the prevalent IIoT layer attacks, common
intrusion methods, and critical threats facing IIoT–edge computing environments. Additionally, we examine various types of cyberattacks targeting CPS, outlining their significant
impact on industrial operations. A detailed taxonomy of primary security mechanisms for
CPS within IIoT–edge computing is developed, followed by a comparative analysis of our
approach against existing research. The findings underscore the widespread vulnerabilities
across the IIoT architecture, particularly in relation to DoS, ransomware, malware, and
MITM attacks. The review emphasizes the integration of advanced security technologies,
including machine learning (ML), federated learning (FL), blockchain, blockchain–ML,
deep learning (DL), encryption, cryptography, IT/OT convergence, and digital twins, as
essential for enhancing the security and real-time data protection of CPS in IIoT–edge computing. Finally, the paper outlines potential future research directions aimed at advancing
cybersecurity in this rapidly evolving domain.
