False Data Injection Attack on Atmospheric Electric Field in Thunderstorm Warning

Document Type

Conference Proceeding

Source of Publication

2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)

Publication Date

8-7-2022

Abstract

Thunderstorm warning plays an important role in lightning prevention and disaster mitigation. In practical applications, thunderstorm warning system is also vulnerable to attacks, such as False Data Injection Attack (FDIA). However, there is a lack of research on False Data Injection Attack for thunderstorm warning. Therefore, this paper put forwards a FDIA method based on principal component analysis (PCA) for atmospheric electric field (AEF), which is usually used for thunderstorm warning. In the FDIA scenario, the AEF-based thunderstorm warning algorithm is also introduced with electric field differential index (EFDI). Finally, experiments are conducted based on AEF data collected by an atmospheric electric field meter (AEFM) about the real thunderstorm. The experimental results show that FDIA seriously interferes with the results of the AEF-based thunderstorm warning.

Publisher

IEEE

Volume

00

First Page

219

Last Page

223

Disciplines

Earth Sciences

Keywords

Meters, Quantum computing, Atmospheric modeling, Lightning, Alarm systems, Data models, Computer crashes

Indexed in Scopus

no

Open Access

no

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