面向智能电网信息物理融合攻击的建模、检测和防御理论与方法

王文婷; 田博彦; 吴法宗; 贺云鹏; 王鑫; 杨明; 冯冬芹

doi:10.11999/JEIT250659

面向智能电网信息物理融合攻击的建模、检测和防御理论与方法

doi: 10.11999/JEIT250659 cstr: 32379.14.JEIT250659

王文婷^{1, 2},
田博彦²,
吴法宗^{3, 4, 5, 6, 7},
贺云鹏^{3, 4, 5, 6, 7},
王鑫^{3, 4, 5, 6, 7, ,},
杨明^{3, 4, 5, 6, 7},
冯冬芹¹

1.
浙江大学控制科学与工程学院杭州 310028
2.
国网山东省电力公司电力科学研究院济南 250003
3.
齐鲁工业大学(山东省科学院) 济南 250014
4.
山东省计算中心(国家超级计算济南中心) 济南 250014
5.
算力互联网与信息安全教育部重点实验室济南 250014
6.
山东省工业网络和信息系统安全重点实验室济南 250014
7.
山东省基础科学研究中心(计算机科学) 济南 250014

基金项目: 国网山东省电力公司科技项目(52062624000C)，浙江大学工业控制技术全国重点实验室开放课题(ICT2025B13)

详细信息

作者简介:
王文婷：女，高级工程师，研究方向为电力系统安全、网络安全

田博彦：男，工程师，研究方向为电力系统

吴法宗：男，博士生，研究方向为深度学习、联邦学习、智能电网安全、信息物理融合攻击检测

贺云鹏：男，助理研究员，博士，研究方向为深度学习、科学机器学习、故障诊断

王鑫：男，特聘研究员，研究方向为人工智能安全、信息物理系统安全

杨明：男，研究员，研究方向为数据安全、人工智能安全

冯冬芹：男，教授，研究方向为工控系统网络安全建模、评估和防护

通讯作者:
王鑫　xinwang@qlu.edu.cn

中图分类号: TN92
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- 被引次数: 0
出版历程
- 收稿日期: 2025-07-14
- 修回日期: 2025-09-28
- 网络出版日期: 2025-10-11
- 刊出日期: 2026-04-10

Modeling, Detection, and Defense Theories and Methods for Cyber-Physical Fusion Attacks in Smart Grid

WANG Wenting^{1, 2},
TIAN Boyan²,
WU Fazong^{3, 4, 5, 6, 7},
HE Yunpeng^{3, 4, 5, 6, 7},
WANG Xin^{3, 4, 5, 6, 7
, ,},
YANG Ming^{3, 4, 5, 6, 7},
FENG Dongqin¹

1.
College of control science and engineering, Zhejiang University, Hangzhou 310027, China
2.
State Grid Shandong Electric Power Research Institute, Jinan 250003, China
3.
Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
4.
Shandong Provincial Computing Center (National Supercomputing Jinan Center), Jinan 250014, China
5.
Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Jinan 250014, China
6.
Shandong Provincial Key Laboratory of Industrial Network and Information System Security, Jinan 250014, China
7.
Shandong Fundamental Research Center for Computer Science, Jinan 250014, China

Funds: State Grid Shandong Municipal Electric Power Company (52062624000C), Zhejiang University State Key Laboratory of Industrial Control Technology Open Project (ICT2025B13)

摘要

摘要: 智能电网(Smart Grid, SG)基于大量传感与检测单元，通过先进的网络通信、监测、调度与优化技术，显著提升了传统电网的管理和调节能力。然而，智能电网的开放性和互联性大幅提高的同时，也加剧了遭受恶意攻击的风险。特别是，攻击者可能通过同时干扰信息层和物理层的感知与决策过程，削弱系统的控制和恢复能力。以往研究通常根据攻击的对象或类型进行分类，而该文提出了一种涵盖智能电网主要组件和通信链路的综合性架构，从整体性的抽象视角对涉及智能电网组件的多种攻击类型进行系统性的信息物理风险评估。此外，该文还从多个角度探讨了智能电网中信息物理融合攻击的检测与防御问题。最后，基于现有的研究进展和趋势，该文对未来智能电网信息物理安全的研究方向进行了讨论与展望。
- 智能电网 /
- 信息物理融合攻击 /
- 攻击建模 /
- 状态估计 /
- 恶意攻击检测
Abstract: Significance Smart Grid (SG), the core of modern power systems, enables efficient energy management and dynamic regulation through cyber-physical integration. However, its high interconnectivity makes it a prime target for cyberattacks, including False Data Injection Attacks (FDIAs) and Denial-of-Service (DoS) attacks. These threats jeopardize the stability of power grids and may trigger severe consequences such as large-scale blackouts. Therefore, advancing research on the modeling, detection, and defense of cyber-physical attacks is essential to ensure the safe and reliable operation of SGs. Progress Significant progress has been achieved in cyber-physical security research for SGs. In attack modeling, discrete linear time-invariant system models effectively capture diverse attack patterns. Detection technologies are advancing rapidly, with physical-based methods (e.g., physical watermarking and moving target defense) complementing intelligent algorithms (e.g., deep learning and reinforcement learning). Defense systems are also being strengthened: lightweight encryption and blockchain technologies are applied to prevention, security-optimized Phasor Measurement Unit (PMU) deployment enhances equipment protection, and response mechanisms are being continuously refined. Conclusions Current research still requires improvement in attack modeling accuracy and real-time detection algorithms. Future work should focus on developing collaborative protection mechanisms between the cyber and physical layers, designing solutions that balance security with cost-effectiveness, and validating defense effectiveness through high-fidelity simulation platforms. This study establishes a systematic theoretical framework and technical roadmap for SG security, providing essential insights for safeguarding critical infrastructure. Prospects Future research should advance in several directions: (1) deepening synergistic defense mechanisms between the information and physical layers; (2) prioritizing the development of cost-effective security solutions; (3) constructing high-fidelity information-physical simulation platforms to support research; and (4) exploring the application of emerging technologies such as digital twins and interpretable Artificial Intelligence (AI).
- Smart Grid (SG) /
- Cyber-physical fusion attacks /
- Attack modeling /
- State estimation /
- Malicious attack detection

HTML全文

图 1 智能电网的一般结构

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图 2 线性时不变系统结构

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图 3 攻击条件下线性时不变系统结构

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表 1 现有文献比较与分析

文献	发表年份	涉及的攻击类型	包含的电网结构	不足
[19]	2020	PMU攻击、状态估计攻击、负载重分配攻击等	变电站、电力市场、发电厂、电力控制单元	未对攻击类型与攻击区域进行分类与总结
[20]	2016	家域网攻击、邻域网攻击、机密性攻击、完整性攻击等	电网通信链路	只考虑智能电网信息层威胁，而忽略了信息物理协同威胁
[21]	2024	机密性攻击、完整性攻击等	SCADA系统	对于智能电网攻击检测方法介绍较为笼统(只有机器学习与区块链)
[22]	2020	拒绝服务攻击、中间人攻击、数据注入攻击	SCADA系统、潮流计算系统等	着重智能电网威胁态势，较少考虑攻击的通用性建模与防御
[23]	2022	时间同步攻击、隐私攻击、阻塞攻击	物联网终端、基站、电网通信链路等	主要考虑网络层威胁，对电网针对性不强
[24]	2019	设备攻击、数据攻击、网络可达性攻击等	变电站、电网控制中心、电网通信链路等	对攻击分类过于笼统、没有总结攻击的共性与特征，防御策略介绍太少
[25]	2024	主动攻击、被动攻击	电网通信链路	对于攻击分类较为笼统，检测方法也只分成已知与未知两种
[26]	2019	数据注入攻击	SCADA系统、远程控制单元、新能源发电、电力市场等	只考虑了错误数据注入攻击一种攻击类型

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表 2 攻击类型与模式

攻击类型	数学模型
错误数据注入攻击	$ {\stackrel{～}{{{\boldsymbol{y}}}}}_{{k}} $=$ {{\boldsymbol{y}}}_{k}+{{\boldsymbol{y}}}_{k}^{\mathrm{a}} $，其中$ {\boldsymbol{y}}_{{k}}^{\mathrm{a}} $表示攻击者设计的错误数据
隐秘攻击	$ {\boldsymbol{u}}_{{k}}^{\mathrm{a}} $$ =M\left({{\boldsymbol{u}}}_{k}\right) $，其中$ M(\cdot ) $表示经过精心设计的攻击模式
重放攻击	$ {{\boldsymbol{y}}}_{k}^{\mathrm{a}}={y}_{k-\tau } $，其中$ \tau $表示重放延迟
拒绝服务攻击	$ \varXi (0,\infty )\triangleq \underset{l\in \mathbb{N}}{\cup }{\mathbb{N}}_{{h}_{l},{h}_{l}+{\tau }_{l}}\in \mathbb{N}$，其中$ {h}_{l} $表示攻击开始时间，$ {\tau }_{l} $表示攻击持续时间

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