TY - GEN
T1 - Cooperative Attack Detection of Power CPS based on Feature Relation Graph Convolutional Network
AU - Li, Da
AU - Shang, Tao
AU - Gao, Xueqin
AU - Tang, Yao
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Cooperative attack is a main threat to power cyber-physical system, which has a high success rate and strong destructiveness. The existing detection methods are limited by a single data type, so it is difficult to detect the combination of cooperative attacks and take defensive measures. In this paper, we propose feature relation graph convolutional network for cooperative attack detection by means of extracting the feature relationship and power node topology relationship. In this method, the power monitoring system data and the communication network data are fused to improve the efficiency of cooperative attack detection. Compared with graph convolutional network, the training time of the proposed method is reduced by 67.78%-94.60% and the detection accuracy is improved by 0.65%-3.41%.
AB - Cooperative attack is a main threat to power cyber-physical system, which has a high success rate and strong destructiveness. The existing detection methods are limited by a single data type, so it is difficult to detect the combination of cooperative attacks and take defensive measures. In this paper, we propose feature relation graph convolutional network for cooperative attack detection by means of extracting the feature relationship and power node topology relationship. In this method, the power monitoring system data and the communication network data are fused to improve the efficiency of cooperative attack detection. Compared with graph convolutional network, the training time of the proposed method is reduced by 67.78%-94.60% and the detection accuracy is improved by 0.65%-3.41%.
KW - Attack Detection
KW - Graph Convolutional Network
KW - Power Cyber-Physical System
UR - https://www.scopus.com/pages/publications/85146117460
U2 - 10.1109/MASS56207.2022.00061
DO - 10.1109/MASS56207.2022.00061
M3 - 会议稿件
AN - SCOPUS:85146117460
T3 - Proceedings - 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2022
SP - 380
EP - 384
BT - Proceedings - 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2022
Y2 - 20 October 2022 through 22 October 2022
ER -