Detection and Identification of Cyber and Physical Attacks on Distribution Power Grids with PVs: An Online High-Dimensional Data-driven Approach.

Journal: IEEE journal of emerging and selected topics in power electronics
Published Date: Sep 24, 2019

Abstract

Cyber and physical attacks threaten the security of distribution power grids. The emerging renewable energy sources such as photovoltaics (PVs) introduce new potential vulnerabilities. Based on the electric waveform data measured by waveform sensors in the distribution power networks, in this paper, we propose a novel high-dimensional data-driven cyber physical attack detection and identification approach (HCADI). Firstly, we analyze the cyber and physical attack impacts (including cyber attacks on the solar inverter causing unusual harmonics) on electric waveforms in distribution power grids. Then, we construct a high dimensional streaming data feature matrix based on signal analysis of multiple sensors in the network. Next, we propose a novel mechanism including leverage score based attack detection and binary matrix factorization based attack diagnosis. By leveraging the data structure and binary coding, our HCADI approach does not need the training stage for both detection and the root cause diagnosis, which is needed for machine learning/deep learning-based methods. To the best of our knowledge, it is the first attempt to use raw electrical waveform data to detect and identify the power electronics cyber/physical attacks in distribution power grids with PVs.

Authors

  • Fangyu Li
    Song are with Center for Cyber-Physical Systems, University of Georgia, Athens, GA 30602, USA.
  • Rui Xie
    Department of Statistics and Data Science, University of Central Florida, Orlando, FL 32816 USA.
  • Bowen Yang
    Song are with Center for Cyber-Physical Systems, University of Georgia, Athens, GA 30602, USA.
  • Lulu Guo
    Song are with Center for Cyber-Physical Systems, University of Georgia, Athens, GA 30602, USA.
  • Ping Ma
    Department of Statistics, University of Georgia, Athens, GA 30602, USA.
  • Jianjun Shi
    H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
  • Jin Ye
    Division of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • WenZhan Song
    Song are with Center for Cyber-Physical Systems, University of Georgia, Athens, GA 30602, USA.

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