Localization of dummy data injection attacks in power systems considering incomplete topological information: A spatio-temporal graph wavelet convolutional neural network approach-Reference-Cited by-同舟云学术

Localization of dummy data injection attacks in power systems considering incomplete topological information: A spatio-temporal graph wavelet convolutional neural network approach

Published:2024-04 Issue: Volume:360 Page:122736
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Qu Zhaoyang,Dong Yunchang,Li Yang,Song Siqi,Jiang Tao,Li Min,Wang Qiming,Wang Lei,Bo Xiaoyong,Zang Jiye,Xu Qi

Funder

Natural Science Foundation of Jilin Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference36 articles.

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2. Method for quantitative estimation of the risk propagation threshold in electric power CPS based on seepage probability[J];Qu;IEEE Access,2018

3. A novel clustering-based method for reliability assessment of cyber-physical microgrids considering cyber interdependencies and information transmission errors[J];Aslani;Appl Energy,2022

4. Detection of false data injection attacks in smart grid: a secure federated deep learning approach[J];Li;IEEE Trans Smart Grid,2022

5. High-stealth false data attacks on overloading multiple lines in power systems[J];Du;IEEE Trans Smart Grid,2022

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