Data Security Defense: Modeling and Detection of Synchrophasor Data Spoofing Attack for Grid Edge

Wei Qiu,He Yin,Yuru Wu,Chujie Zeng,Chang Chen,Yuqing Dong,Yilu Liu

IEEE PES Innovative Smart Grid Technologies Conference (ISGT)（2024）

The University of Tennessee

Cited 0|Views14

Abstract

Data security and cyberattack have become critical issues in the distributed power system where adversaries can swap the source information of sensors or even spoof and alter measurements. However, the cyber security of the power system is challenged by the unpredictability and stealth of the spoofing attacks. To protect the data security at the grid edge, this paper developed a synchrophasor data spoofing attack detection framework based on the time-frequency feature extraction techniques including the short-time Fourier transform (STFT) and object detection network for real-time synchrophasor data categorization and spoofing attack localization. The proposed approach outperforms earlier work in terms of spoofing attack detection and offers a vital localization function employing distributed synchrophasor sensors.

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Key words

Data security defense,synchrophasor data,spoofing attack,time-frequency domain,grid edge

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【要点】：本文提出了一种基于时间-频率特征提取技术的同步相量数据欺骗攻击检测框架，包括短时傅里叶变换（STFT）和目标检测网络，以实现实时同步相量数据的分类和欺骗攻击的定位，创新之处在于优异的欺骗攻击检测性能和利用分布式同步相量传感器的关键定位功能。

【方法】：采用了基于时间-频率特征提取的方法，结合了短时傅里叶变换（STFT）和目标检测网络。

【实验】：通过构建基于同步相量数据欺骗攻击的检测框架，在实时数据上进行实验，使用分布式同步相量传感器进行数据采集，实验结果显示该方法在欺骗攻击检测方面优于先前的工作，并能够有效地定位攻击。