标题： 分布式弹性状态估计与控制及战略性实施的安全措施 显示英文标题

标题： Distributed Resilient State Estimation and Control with Strategically Implemented Security Measures

摘要： 本文解决了在存在恶意虚假数据注入传感器攻击和有界噪声的情况下，线性时不变系统的分布式弹性状态估计与控制问题。 我们考虑一个系统操作员（防御者）能够部署网络安全措施来应对传感器被入侵的情况。 尽管此类措施可以增强对对抗性攻击的弹性，但可能会产生高昂的成本；因此，战略性地选择对策以平衡弹性收益和成本效率至关重要。 我们首先证明，通过适当实施安全措施，系统的抗攻击弹性达到最大，这意味着没有任何攻击者可以执行不可检测的传感器攻击。 在此分析基础上，我们提出了一种算法，用于识别最优的安全措施。 虽然确定此措施在一般情况下是NP难的，但我们还推导出了在这些条件下可以进行高效计算的充分条件。 此外，我们开发了一种由最优安全措施指导的分布式弹性状态估计和控制方案，并建立了保证估计和控制误差有界的条件。 最后，我们通过车辆编队场景的数值仿真验证了我们方法的有效性。 显示英文摘要

摘要： This paper addresses the problem of distributed resilient state estimation and control for linear time-invariant systems in the presence of malicious false data injection sensor attacks and bounded noise. We consider a system operator (defender) capable of deploying cybersecurity measures to counteract the sensor compromises. Although such measures enhance resilience against adversarial attacks, they may incur substantial costs; hence, it is crucial to select countermeasures to balance resilience gains and cost efficiency strategically. We first demonstrate that the system's resilience against attacks is maximized through the appropriate implementation of security measures, implying that no attacker can execute undetectable sensor attacks. Building on this analysis, we propose an algorithm that identifies the optimal security measure. While determining this measure is NP-hard in general, we also derive sufficient conditions under which efficient computation is feasible. Furthermore, we develop a distributed resilient state estimation and control scheme informed by the optimal security measure and establish conditions that guarantee bounded estimation and control errors. Finally, we validate the efficacy of our approach via numerical simulations of a vehicle platooning scenario.