A hybrid stochastic game for secure control of cyber-physical systems
A hybrid stochastic game for secure control of cyber-physical systems
复制标题
用于安全控制网络物理系统的混合随机博弈
DOI：
10.1016/j.automatica.2018.03.012
复制
发表时间：
2018
期刊：
影响因子：
6.4
通讯作者：
Pappas, George J.
中科院分区：
文献类型：
--
作者：
Miao, Fei;Zhu, Quanyan;Pajic, Miroslav;Pappas, George J.
在本文中，我们建立了一个零和，混合状态随机博弈模型设计防御策略的网络物理系统对不同类型的攻击。随着当今网络物理系统（CPS）的日益集成，安全性是关键基础设施的一个挑战。虽然针对特定攻击模型的弹性控制和检测技术已经被提出，但要分析和设计针对CPS的多种类型攻击的检测和防御机制，需要新的系统框架。除了安全性，还需要考虑其他要求，如最优控制成本。我们提出的混合博弈模型包含由系统动力学描述的物理状态，以及代表由一组子系统组成的系统的检测模式的网络状态。一个策略意味着选择一个子系统，结合一个控制器，一个估计器和一个检测器之间的一组有限的候选组件在每个状态。在此博弈模型的基础上，提出了有限时间博弈的一个次优值迭代算法，并证明了该算法可得到有限时间博弈的值的一个上界。一个移动的地平线的方法也被开发，以提供一个可扩展的和实时的计算的切换策略。这两种算法的目的是获得一个鞍点平衡策略，平衡系统的安全开销和控制成本。本文说明了这些概念，使用数值例子，我们与以前的系统设计，只配备了一种类型的控制器的结果进行比较。
In this paper, we establish a zero-sum, hybrid state stochastic game model for designing defense policies for cyber-physical systems against different types of attacks. With the increasingly integrated properties of cyber-physical systems (CPS) today, security is a challenge for critical infrastructures. Though resilient control and detecting techniques for a specific model of attack have been proposed, to analyze and design detection and defense mechanisms against multiple types of attacks for CPSs requires new system frameworks. Besides security, other requirements such as optimal control cost also need to be considered. The hybrid game model we propose contains physical states that are described by the system dynamics, and a cyber state that represents the detection mode of the system composed by a set of subsystems. A strategy means selecting a subsystem by combining one controller, one estimator and one detector among a finite set of candidate components at each state. Based on the game model, we propose a suboptimal value iteration algorithm for a finite horizon game, and prove that the algorithm results an upper bound for the value of the finite horizon game. A moving-horizon approach is also developed in order to provide a scalable and real-time computation of the switching strategies. Both algorithms aim at obtaining a saddle-point equilibrium policy for balancing the system’s security overhead and control cost. The paper illustrates these concepts using numerical examples, and we compare the results with previously system designs that only equipped with one type of controller.
随机游戏中的快速规划
DOI：
--
发表时间：
2000
期刊：
Conference on Uncertainty in Artificial Intelligence
影响因子：
--
作者：
M. Kearns;Y. Mansour;Satinder Singh
通讯作者：
Satinder Singh