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Title: Model-Free Data Authentication for Cyber Security in Power Systems

Abstract

With the development and wide deployment of measurement equipment, data can be automatically measured and visualized for situation awareness in power systems. However, the cyber security of power systems is also threated by data spoofing attacks. This letter proposed a measurement data source authentication (MDSA) algorithm based on feature extraction techniques including ensemble empirical mode decomposition (EEMD) and fast Fourier transform (FFT), and machine learning for real-time measurement data classification. Compared with previous work, the proposed algorithm can achieve higher accuracy of MDSA using a shorter window of data from closely located synchrophasor measurement sensors.

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]; ORCiD logo [2]; ORCiD logo [2]
  1. Zhejiang Univ. of Technology, Hangzhou (China); Univ. of Tennessee, Knoxville, TN (United States)
  2. Univ. of Tennessee, Knoxville, TN (United States)
  3. Zhejiang Univ. of Technology, Hangzhou (China)
  4. Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE; National Science Foundation (NSF); China Scholarship Council (CSC)
OSTI Identifier:
1770637
Grant/Contract Number:  
AC05-00OR22725; 1931975; EEC-1041877
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Smart Grid
Additional Journal Information:
Journal Volume: 11; Journal Issue: 5; Journal ID: ISSN 1949-3053
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; cyber security; data authentication; ensemble empirical mode decomposition (EEMD); fast Fourier transform (FFT); back propagation (BP) network

Citation Formats

Liu, Shengyuan, You, Shutang, Yin, He, Lin, Zhenzhi, Liu, Yilu, Yao, Wenxuan, and Sundaresh, Lakshmi. Model-Free Data Authentication for Cyber Security in Power Systems. United States: N. p., 2020. Web. doi:10.1109/tsg.2020.2986704.
Liu, Shengyuan, You, Shutang, Yin, He, Lin, Zhenzhi, Liu, Yilu, Yao, Wenxuan, & Sundaresh, Lakshmi. Model-Free Data Authentication for Cyber Security in Power Systems. United States. https://doi.org/10.1109/tsg.2020.2986704
Liu, Shengyuan, You, Shutang, Yin, He, Lin, Zhenzhi, Liu, Yilu, Yao, Wenxuan, and Sundaresh, Lakshmi. Wed . "Model-Free Data Authentication for Cyber Security in Power Systems". United States. https://doi.org/10.1109/tsg.2020.2986704. https://www.osti.gov/servlets/purl/1770637.
@article{osti_1770637,
title = {Model-Free Data Authentication for Cyber Security in Power Systems},
author = {Liu, Shengyuan and You, Shutang and Yin, He and Lin, Zhenzhi and Liu, Yilu and Yao, Wenxuan and Sundaresh, Lakshmi},
abstractNote = {With the development and wide deployment of measurement equipment, data can be automatically measured and visualized for situation awareness in power systems. However, the cyber security of power systems is also threated by data spoofing attacks. This letter proposed a measurement data source authentication (MDSA) algorithm based on feature extraction techniques including ensemble empirical mode decomposition (EEMD) and fast Fourier transform (FFT), and machine learning for real-time measurement data classification. Compared with previous work, the proposed algorithm can achieve higher accuracy of MDSA using a shorter window of data from closely located synchrophasor measurement sensors.},
doi = {10.1109/tsg.2020.2986704},
journal = {IEEE Transactions on Smart Grid},
number = 5,
volume = 11,
place = {United States},
year = {2020},
month = {4}
}

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