Detection of Faults and Attacks Including False Data Injection Attack in Smart Grid Using Kalman Filter

By Kebina Manandhar, Xiaojun Cao, Fei Hu, Yao Liu. IEEE Transactions on Control of Network Systems, 2014

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Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach (2022, methodology): “And many studies on methods for DC state estimation have subsequently emerged, such as DC FDIA detection by Kalman filtering [8], network theory [9], [10], and machine learning [11].”
A Survey on the Detection Algorithms for False Data Injection Attacks in Smart Grids (2020, methodology): “Similar approaches were taken in [61], [62].”
Online False Data Injection Attack Detection With Wavelet Transform and Deep Neural Networks (2018, methodology): “Specifically, the methods proposed in [18] and [19] are implemented and tested with the same data.”
A Survey on Security Communication and Control for Smart Grids Under Malicious Cyber Attacks (2019, methodology): “These detection methods can be used in SG [79], [83].”
Input-to-State Stabilizing Control for Cyber-Physical Systems With Multiple Transmission Channels Under Denial of Service (2018, neutral): “…understealthydeceptionattacks[11],Kalmanﬁlter-basedattacksde-tection[12],andremotestateestimation[13],justtonameafew.”