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面向参数化ε-隐匿性的远程状态估计最优隐匿攻击

Optimal Stealthy Attack Against Remote State Estimation With Parameterized $\epsilon$-Stealthiness

作者 Li-Wei Mao · Guang-Hong Yang
期刊 IEEE Transactions on Industrial Informatics
出版日期 2025年12月
卷/期 第 22 卷 第 2 期
技术分类 控制与算法
技术标签 模型预测控制MPC 故障诊断 强化学习 智能化与AI应用
相关度评分 ★★★ 3.0 / 5.0
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中文摘要

本文研究网络物理系统中针对远程状态估计的隐匿攻击设计问题,提出参数化ε-隐匿性概念以降低检测器误报率,并构建基于历史残差信息的单参数步进攻击模型,给出最优攻击策略。仿真验证了其在保证隐匿性前提下的性能劣化能力。

English Abstract

In this article, we investigate the problem of designing stealthy attack against remote state estimation in cyber-physical systems, where the attacker intends to maximize the deterioration of the estimation performance while remaining stealthy. To enable the attack to bypass the detector with a lower alarm rate, a notion of parameterized $\epsilon$-stealthiness is introduced. Within the framework, a novel attack model is proposed, where all the available historical innovations are utilized and only one attack parameter needs to be designed at each step. Subsequently, the optimal attack strategy is presented. Compared to the existing results, the proposed attack strategy can be designed with fewer parameters while guaranteeing the desired attack performance. Simulations are given to verify the validity of the results.
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SunView 深度解读

该文聚焦于CPS中状态估计的隐蔽攻击建模与防御理论,虽非直接面向光伏/储能硬件,但对阳光电源iSolarCloud智能运维平台的异常检测、ST系列PCS及PowerTitan储能系统的安全状态感知具有启示意义。建议将ε-隐匿性分析框架融入iSolarCloud的AI告警抑制模块,提升对恶意数据注入攻击(如虚假功率上传、SOC欺骗)的鲁棒性;同时可指导构网型GFM逆变器在弱电网下的可信状态估计设计。