An Intelligent Edge-Cloud Collaborative Framework for Communication Security in Distributed Cyber-Physical Systems

The rapid growth of IoT (Internet of Things) and smart services facilitate many CPS (Cyber-Physical Systems) such as smart health, smart grid and so on. Nevertheless, the communication security issues in CPS are becoming more and more important with the growing complexity of the CPS network and the increasing dependency of critical network infrastructure on cyber-based technologies. In recent years, deep learning technology has shown its superiority in detecting communication security attacks, but its high computational complexity and the massive amount of data generated by IoT devices have brought challenges to traditional cloud computing technology in terms of bandwidth and computing resources. In this paper, we have analyzed the characteristics of heterogeneity and hierarchy in attacks on CPS. We have also analyzed the role of edge intelligence in handling the security of large-scale data communication in CPS. Furthermore, we proposed a CPS communication attack detection framework based on edge cloud collaboration, aiming to improve the parallel efficiency of hardware resources when executing detection tasks. We aim to enhance the intelligence of physical devices and the degree of cloud collaboration, satisfying the real-time processing requirements of large-scale, hierarchical CPS attack detection. Furthermore, through simple simulation experiments, we verified the effectiveness of the proposed edge cloud collaboration framework in CPS attack detection.