Scinovex
articleTop 1% cited

False Data Injection on State Estimation in Power Systems—Attacks, Impacts, and Defense: A Survey

IEEE Transactions on Industrial Informatics · 2016 · Vol. 13(2) · pp. 411–423
Ruilong DengGaoxi XiaoRongxing LuHao LiangAthanasios V. Vasilakos

Abstract

The accurately estimated state is of great importance for maintaining a stable running condition of power systems. To maintain the accuracy of the estimated state, bad data detection (BDD) is utilized by power systems to get rid of erroneous measurements due to meter failures or outside attacks. However, false data injection (FDI) attacks, as recently revealed, can circumvent BDD and insert any bias into the value of the estimated state. Continuous works on constructing and/or protecting power systems from such attacks have been done in recent years. This survey comprehensively overviews three major aspects: constructing FDI attacks; impacts of FDI attacks on electricity market; and defending against FDI attacks. Specifically, we first explore the problem of constructing FDI attacks, and further show their associated impacts on electricity market operations, from the adversary's point of view. Then, from the perspective of the system operator, we present countermeasures against FDI attacks. We also outline the future research directions and potential challenges based on the above overview, in the context of FDI attacks, impacts, and defense.

Smart Grid Security and ResilienceNetwork Security and Intrusion DetectionInternet Traffic Analysis and Secure E-votingAdversaryContext (archaeology)Computer securityState (computer science)Computer scienceElectric power systemElectricityPower (physics)EstimationEngineering

Funding

  • Alberta Innovates - Technology Futures
  • Natural Sciences and Engineering Research Council of Canada
Citations
537
FWCI
32.21
field-weighted impact
References
97
Percentile
100%
vs. same field & year
Citations per year
Cited by
A Survey on the Detection Algorithms for False Data Injection Attacks in Smart Grids
IEEE Transactions on Smart Grid · 2019 · 676 citations
Online False Data Injection Attack Detection With Wavelet Transform and Deep Neural Networks
IEEE Transactions on Industrial Informatics · 2018 · 376 citations
References
A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches
IEEE Transactions on Industrial Informatics · 2015 · 906 citations
Malicious Data Attacks on the Smart Grid
IEEE Transactions on Smart Grid · 2011 · 792 citations
Integrity Data Attacks in Power Market Operations
IEEE Transactions on Smart Grid · 2011 · 485 citations
Smart Grid Technologies: Communication Technologies and Standards
IEEE Transactions on Industrial Informatics · 2011 · 2,609 citations
Modeling Load Redistribution Attacks in Power Systems
IEEE Transactions on Smart Grid · 2011 · 533 citations
Strategic Protection Against Data Injection Attacks on Power Grids
IEEE Transactions on Smart Grid · 2011 · 582 citations
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.