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Detection of False Data Injection Attacks on Smart Grids: A Resilience-Enhanced Scheme.

Authors :
Li, Beibei
Lu, Rongxing
Xiao, Gaoxi
Li, Tao
Choo, Kim-Kwang Raymond
Source :
IEEE Transactions on Power Systems. Jul2022, Vol. 37 Issue 4, p2679-2692. 14p.
Publication Year :
2022

Abstract

The integration of phasor measurement units (PMUs) and phasor data concentrators (PDCs) in smart grids may be exploited by attackers to initiate new and sophisticated false data injection (FDI) attacks. Existing FDI attack mitigation approaches are generally less effective against sophisticated FDI attacks, such as collusive false data injection (CFDI) attacks launched by compromised PDCs (and PMUs) as we demonstrate in this paper. Thus, we propose a secure and resilience-enhanced scheme (SeCDM) to detect and mitigate such cyber threats in smart grids. Specifically, we design a decentralized homomorphic computation paradigm along with a hierarchical knowledge sharing algorithm to facilitate secure ciphertext calculation of state estimation residuals. Following this, a centralized FDI detector is implemented to detect FDI attacks. Findings from the security analysis demonstrate our approach achieves enhanced conventional FDI and CFDI attack resilience, and findings from our performance evaluations on the standard IEEE 14-, 24-, and 39-bus power systems also show that the communication overheads and computational complexity are reasonably “low”. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08858950
Volume :
37
Issue :
4
Database :
Academic Search Index
Journal :
IEEE Transactions on Power Systems
Publication Type :
Academic Journal
Accession number :
157551987
Full Text :
https://doi.org/10.1109/TPWRS.2021.3127353