Model-Free False Data Injection Attack in Networked Control Systems: A Feedback Optimization Approach

• 成果类型: Article
• 署名作者: Luo, Xiaoyu; Fang, Chongrong; He, Jianping; Zhao, Chengcheng; Paccagnan, Dario
• 署名单位: Shanghai Jiao Tong University; Zhejiang University; Zhejiang University; Imperial College London
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3442956
• 发表日期: 2025
• 页码: 783-798
• 关键词: Optimization; trajectory; system dynamics; steady-state; Analytical models; linear programming; Cyberattack; data-driven; false data injection (FDI) attacks; zeroth-order feedback optimization

摘要

Security issues have gathered growing interest within the control systems community, as physical components and communication networks are increasingly vulnerable to cyber attacks. In this context, recent literature has studied increasingly sophisticated false data injection attacks, with the aim to design mitigative measures that improve the systems' security. Notably, data-driven attack strategies-whereby the system dynamics is oblivious to the adversary-have received increasing attention. However, many of the existing works on the topic rely on the implicit assumption of linear system dynamics, significantly limiting their scope. Contrary to that, in this work, we design and analyze a truly model-free false data injection attack that applies to general linear and nonlinear systems. More specifically, we aim at designing an injected signal that steers the output of the system toward a (maliciously chosen) trajectory. We do so by designing a zeroth-order feedback optimization policy and jointly using probing signals for real-time measurements. We then characterize the quality of the proposed model-free attack through its optimality gap, which is affected by the dimensions of the attack signal, the number of iterations performed, and the convergence rate of the system. Finally, we extend the proposed attack scheme to systems with internal noise. Extensive simulations show the effectiveness of the proposed attack scheme.