PDL: An Efficient Prediction-Based False Data Injection Attack Detection and Location in Smart Grid

Wanjiao Shi, Yufeng Wang, Qun Jin, Jianhua Ma

研究成果

8 被引用数 (Scopus)

抄録

With the rapid development of Internet of Things (IOT) technologies, modern power systems have become complex cyber-physical systems. A large number of smart devices have promoted efficient generation, transmission and distribution in the smart grid. State estimation (SE) is one of fundamental components in smart grid that evaluates the operation state of a grid by using a set of sensor measurements and grid topologies. A major issue is the authenticity of the measurements collected by the sensors. Specifically, the false data injection attack (FDIA) aims to temper the information that reflect the grid operation state. In this paper, we propose an efficient prediction-based FDIA detection and location scheme, PDL, in which the state vector of smart grid can be represented as multivariate time series, and can be predicted by vector autoregressive processes (VAR) through intentionally exploiting the temporal and spatial correlations of states. Different from most previous works which assumed the state transfer matrix constant and diagonal, a time-varying and non-diagonal matrix is adopted in this scheme. Then, the consistency between the predicted measurements and the observed measurements is utilized to detect and locate abnormal data. Besides, the detected abnormal data can be replaced with the predicted data, which simplifies the calibration process. Extensive simulation results verify the performance of the proposed scheme.

本文言語English
ホスト出版物のタイトルProceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018
編集者Claudio Demartini, Sorel Reisman, Ling Liu, Edmundo Tovar, Hiroki Takakura, Ji-Jiang Yang, Chung-Horng Lung, Sheikh Iqbal Ahamed, Kamrul Hasan, Thomas Conte, Motonori Nakamura, Zhiyong Zhang, Toyokazu Akiyama, William Claycomb, Stelvio Cimato
出版社IEEE Computer Society
ページ676-681
ページ数6
ISBN(電子版)9781538626665
DOI
出版ステータスPublished - 2018 6 8
イベント42nd IEEE Computer Software and Applications Conference, COMPSAC 2018 - Tokyo, Japan
継続期間: 2018 7 232018 7 27

出版物シリーズ

名前Proceedings - International Computer Software and Applications Conference
2
ISSN(印刷版)0730-3157

Other

Other42nd IEEE Computer Software and Applications Conference, COMPSAC 2018
国/地域Japan
CityTokyo
Period18/7/2318/7/27

ASJC Scopus subject areas

  • ソフトウェア
  • コンピュータ サイエンスの応用

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