ABSTRACT
Smart grids, industrial automation, autonomous vehicles, and healthcare systems are merely some of the applications that have been made accessible by the development of cyber-physical systems. Due to their complex and distributed nature, these systems are open to several methods of assault. To ensure both the safety and reliability of the system, cyberspace-physical system security must be responded to from both the cyber and physical perspectives. The use of diverse security approaches will safeguard cyber-physical systems. Furthermore, in order to safeguard CPSs from fraudulent activities, techniques for detecting cyberattacks must be developed. By matching the existing activity with the anticipated conduct predicted by earlier information or already established rules, anomaly detection models are able to detect attacks. If these attacks are not rapidly identified, they may cause a catastrophic impact on the physical system. Anomaly-detection models, signature-based surveillance models, rule-based detection models, and machine learning–based attack analyzers are only a handful of the attack-detection models that have been produced in order to detect breaches on CPSs.
