Active and passive hybrid detection method for power CPS false data injection attacks with improved AKF and GRU‐CNN-Reference-Cited by-同舟云学术

Active and passive hybrid detection method for power CPS false data injection attacks with improved AKF and GRU‐CNN

Published:2022-02-24 Issue:7 Volume:16 Page:1490-1508
ISSN:1752-1416
Container-title:IET Renewable Power Generation
language:en
Short-container-title:IET Renewable Power Gen

Author:

Qu Zhaoyang¹²,Bo Xiaoyong¹³²^ORCID,Yu Tong⁴,Liu Yaowei⁵,Dong Yunchang¹²^ORCID,Kan Zhongfeng⁶,Wang Lei¹²,Li Yang¹

Affiliation:

1. School of Electrical Engineering Northeast Electric Power University Jilin China

2. Jilin Province Engineering Technology Research Center of Power Big Data Intelligent Processing Jilin China

3. Electrical and Information Engineering College Jilin Agricultural Science and Technology University Jilin China

4. Electric Power Research Institute China Southern Power Grid Guangxi Power Grid Co., Ltd. Nanning China

5. State Grid Jilin Electric Power Co., Ltd. Changchun China

6. State Grid Jilin Electric Power Co. Ltd. Jilin Power Supply Company Jilin China

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/rpg2.12432

Reference44 articles.

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2. Method for Quantitative Estimation of the Risk Propagation Threshold in Electric Power CPS Based on Seepage Probability

3. Multi‐objective optimization model of electricity consumption behavior considering combination of household appliance correlation and comfort;Qu Z.Y.;Autom. Electr. Power Syst.,2018

4. An accurate traffic classification model based on support vector machines

5. Cyber-Physical Modeling and Cyber-Contingency Assessment of Hierarchical Control Systems

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