Research on Power Information Network Attack Detection Method Combining Multiple Kalman Filter Algorithms

In order to further improve the attack detection level of power information network, this paper proposes an attack detection method based on improved cubature Kalman filter (ICKF) to detect false data injection attacks. Among them, the cubature Kalman filter algorithm (CKF) is selected as the basic...

Full description

Saved in:
Bibliographic Details
Published in2023 7th Asian Conference on Artificial Intelligence Technology (ACAIT) pp. 1169 - 1173
Main Authors Hu, Zheng, Tang, Yong, Gou, Xiang
Format Conference Proceeding
LanguageEnglish
Published IEEE 10.11.2023
Subjects
Detection algorithms
false data injection attack
Filtering algorithms
Information filters
Kalman filter
Kalman filters
power information network
Security
Simulation
State estimation
Online AccessGet full text
DOI10.1109/ACAIT60137.2023.10528419

Cover

More Information
Summary:In order to further improve the attack detection level of power information network, this paper proposes an attack detection method based on improved cubature Kalman filter (ICKF) to detect false data injection attacks. Among them, the cubature Kalman filter algorithm (CKF) is selected as the basic detection algorithm, and it is improved to further improve its detection performance. Simulation results show that compared with other state estimation algorithms, ICKF can estimate the state of power information system more accurately, and its average absolute error is only 2.0124%. In addition, the attack detection method based on ICKF can effectively detect the false data injection attacks. Therefore, the designed detection method based on ICKF can effectively detect false data injection attacks, which further ensures the security of power information, and has certain practical application value.
DOI:10.1109/ACAIT60137.2023.10528419