近期，实验室吴承伟作为第一作者，姚蔚然作为通讯作者的论文“Secure Control for Cyber-Physical Systems under Malicious Attacks”被国际期刊IEEE Transactions on Control of Network Systems录用。

该论文针对虚假数据注入攻击情形下的信息物理系统，基于系统可控性构建了一组不可预测的移动目标防御序列，提出了一种基于移动目标防御的主动防御安全控制算法，设计了基于零和博弈的强化学习控制策略应对移动目标防御序列失效情形。其创新性体现在：该成果设计了主动防御策略，解决了随时间推移攻击者攻击优势逐渐增加的问题，大幅提升了系统的安全性。

Abstract

This paper investigates the secure control problem for cyber-physical systems when the malicious data is injected into the cyber realm which is directly connecting to the actuators. Based on moving target defense and reinforcement learning, we propose a novel proactive and reactive defense control scheme. First, the system (A; B) is modeled as a switching system consisting of several controllable pairs (A; Bl) to facilitate the construction of the moving target defense control scheme. The controllable pairs (A; Bl) can be altered to update system dynamics under certain unpredictable switching probabilities for each subsystem, which can prevent the adversaries from effective attacks. Second, both attack detection and isolation schemes are designed to accurately locate and exclude the compromised actuators from a switching sequence. Third, a reinforcement learning algorithm based on the zero-sum game theory is proposed to design the defense control scheme when there exist no controllable subsystems to switch. To demonstrate the effectiveness of the defense control scheme, a three-tank system under unknown cyber attacks is illustrated.