Gaussian Filtering With Cyber-Attacked Data

Kumar, Guddu; Naik, Amit Kumar; Swaminathan, R.; Singh, Abhinoy Kumar (2024-01-22)
 
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https://doi.org/10.1109/LSP.2024.3356825

Kumar, Guddu
Naik, Amit Kumar
Swaminathan, R.
Singh, Abhinoy Kumar
IEEE
22.01.2024

G. Kumar, A. K. Naik, S. R and A. K. Singh, "Gaussian Filtering With Cyber-Attacked Data," in IEEE Signal Processing Letters, vol. 31, pp. 546-550, 2024, doi: 10.1109/LSP.2024.3356825

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doi:https://doi.org/10.1109/LSP.2024.3356825
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https://urn.fi/URN:NBN:fi:oulu-202403212381
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Abstract

Gaussian filtering is a commonly used nonlinear filtering method. This letter proposes an advanced Gaussian filtering method for handling cyber-attacked measurement data. It considers three general forms of measurement data irregularities due to the attack, including false data injection (FDI), time asynchronous measurements (TAM), and denial-of-service (DoS). The proposed method introduces a modified measurement model to incorporate the possibility of these irregularities occurring simultaneously. Subsequently, it re-derives the traditional Gaussian filtering for the modified measurement model, resulting in the proposed filtering method. The improved accuracy of the proposed method is validated for two simulation problems.
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