Xia, M, Du, D, Fei, M et al. (1 more author) (2021) Impact Analysis of False Data Injection Attack on Smart Grid State Estimation Under Random Packet Losses. In: Communications in Computer and Information Science. LSMS 2020, ICSEE 2020: Recent Featured Applications of Artificial Intelligence Methods. LSMS 2020 and ICSEE 2020 Workshops, 25 Oct 2020, Hangzhou, China. Springer , pp. 61-75. ISBN 978-981-33-6377-9
Abstract
Supervisory control and data acquisition (SCADA) system has been widely used in traditional power systems for operation and control. As increasingly more ICT technologies are deployed to improve the smartness of the power grid, cyber security is becoming an important issue in the development of smart grids, for example, false data injection attack (FDIA) poses a serious threat. The paper analyzes the impact of false data injection attack on smart grid state estimation under random packet losses. First, a measurement model of power grids under random packet loss is established, and an attack vector range that can fool the attack detector is acquired. Then, a mean square error matrix of weighted least squares estimation is proposed, taking into account potential false data injection attacks. A IEEE-14 nodes system is used to evaluate the performance of the weighted least squares state estimation under three different scenarios, namely false data injection attack only, random packet loss only, and under both random packet loss and false data injection attack.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Nature Singapore Pte Ltd. 2020. This is an author produced version of a conference paper published in Communications in Computer and Information Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | False data injection attack; Random packet losses; Weighted least squares estimation; Smart grid |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Mar 2021 16:41 |
Last Modified: | 25 May 2021 10:37 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-981-33-6378-6_5 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:171786 |