智能电网运动目标防御的隐身性与有效性研究

IF 9.9 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

IEEE Transactions on Industrial Informatics Pub Date : 2025-01-27 DOI:10.1109/TII.2024.3514211

Jiazhou Wang;Jue Tian;Gaoxi Xiao;Yang Liu;Hao Huang;Yadong Zhou;Ting Liu

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引用次数: 0

摘要

最近的研究提出了移动目标防御（MTD）来检测电网中的虚假数据注入（FDI）攻击。为了使MTD的激活不被攻击者发现，提出了一种隐藏MTD (hidden MTD， HMTD)，它使MTD后的系统潮流保持不变。事实证明，由于其隐身性要求，HMTD无法检测到所有的FDI攻击。然而，MTD隐身性的数学机制尚未揭示。HMTD的最大探测能力也不清楚。为了解决上述问题，我们首先分析了基于图论的HMTD的最大检测能力，并提出了实现该能力的拓扑条件。此外，我们研究了HMTD的基本特征，发现所有的HMTD方案都在分支参数张成的空间中。我们进一步提出了一种多阶段HMTD （MHMTD）方法，在该空间中选择多个HMTD方案以最大化检测能力。实验表明，MHMTD在所有测试系统中都能最大限度地提高HMTD的检测能力，具有较高的隐身概率。

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On Stealthiness and Effectiveness of Moving Target Defense in Smart Grids

Recent studies have proposed moving target defense (MTD) to detect false data injection (FDI) attacks in power grids. To hide the activation of MTD from attackers, a hidden MTD (HMTD) has been proposed, which keeps the system power flow after MTD unchanged. It has been proved that HMTD cannot detect all FDI attacks because of its stealthiness requirements. However, the mathematical mechanism of MTD's stealthiness has yet to be revealed. The maximum detection capability of HMTD is also unclear. To address the abovementioned issues, we first analyze the maximum detection capability of HMTD based on graph theory and propose the topological condition to achieve it. Moreover, we study the essential characteristics of HMTD and find that all HMTD schemes are in a space spanned by branch parameters. We further propose a multistage HMTD (MHMTD) method to select multiple HMTD schemes in this space to maximize the detection capability. Experiments show that the MHMTD can maximize the detection capability of HMTD in all test systems with high stealthy probability.

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来源期刊

IEEE Transactions on Industrial Informatics 工程技术-工程：工业

CiteScore

24.10

自引率

8.90%

发文量

1202

审稿时长

5.1 months

期刊介绍： The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.