A Data-Driven Encrypted Transmission and Security Monitoring Approach for Cyber-Physical Systems

This article designs a data-driven security defense and monitoring approach that involves encrypted transmission and attack detection to defend cyber-physical systems (CPS) against stealthy attacks. The approach starts by using subspace theory to achieve data-driven coprime factorization of the closed-loop CPS. Based on this, the physical dynamics are encrypted from a control perspective to minimize the risk of information leakage and hinder the creation of stealthy attacks. Meanwhile, the security monitoring approach is designed using the same offline-learned coprime factorization. This approach is effective in detecting and distinguishing between cyber-physical attacks and machine-induced faults, which enables effective maintenance measures to be taken for different anomalies. The proposed encrypted transmission and security monitoring approach provides a comprehensive defense against nonstealthy and stealthy attacks. The effectiveness of our work is illustrated through a numerical example and experimental results on a Mecanum-wheeled vehicle platform.