In this paper, we develop a completely model-free moving target defense framework for the detection and mitigation of sensor and/or actuator attacks in cyber–physical systems with dynamics that evolve in discrete-time. We incorporate an intrusion detection mechanism based on an approximate dynamic programming technique that learns the policies for optimal regulation and optimal tracking while simultaneously defending against actuator and sensor attacks in a model-free fashion. Switching rules are leveraged to force proactive and reactive defense mechanisms as well as, guarantee the stability of the equilibrium point. Finally, as a case study, we apply the proposed moving target defense framework to a DC–DC converter that is used in electric vehicles.

在本文中，我们开发了一种完全无模型的移动目标防御框架，用于检测和缓解具有离散时间动态变化的网络物理系统中的传感器和/或执行器攻击。我们采用了一种基于近似动态编程技术的入侵检测机制，该机制可学习优化调节和最优跟踪的策略，同时以无模型的方式防御执行器和传感器的攻击。转换规则被用来强制主动和被动防御机制，并保证平衡点的稳定性。最后，作为案例研究，我们将提出的移动目标防御框架应用于电动汽车中使用的DC-DC转换器。