论文标题
规避风险控制器设计针对对执行器的数据注射攻击的不确定控制系统的攻击
Risk-averse controller design against data injection attacks on actuators for uncertain control systems
论文作者
论文摘要
在本文中，我们考虑了针对对不确定控制系统的执行器的数据注射攻击的最佳控制器设计问题。我们考虑旨在最大化攻击影响的攻击，同时在有限的视野中保持隐秘。为此，我们使用有条件的价值风险来表征与攻击影响相关的风险。使用最近提出的输出$ \ ell_2 $ - gain（OOG）的最坏情况攻击影响的特征是。我们制定了设计问题，并观察到它是非凸面且难以解决的。使用基于方案的优化框架和OOG的凸代理，我们提出了一个凸优化问题，该问题近似于使用概率证书解决设计问题。最后，我们通过数值示例来说明结果。
In this paper, we consider the optimal controller design problem against data injection attacks on actuators for an uncertain control system. We consider attacks that aim at maximizing the attack impact while remaining stealthy in the finite horizon. To this end, we use the Conditional Value-at-Risk to characterize the risk associated with the impact of attacks. The worst-case attack impact is characterized using the recently proposed output-to-output $\ell_2$-gain (OOG). We formulate the design problem and observe that it is non-convex and hard to solve. Using the framework of scenario-based optimization and a convex proxy for the OOG, we propose a convex optimization problem that approximately solves the design problem with probabilistic certificates. Finally, we illustrate the results through a numerical example.
