DocumentCode :
70894
Title :
Detection of false data injection attacks in smart-grid systems
Author :
Po-Yu Chen ; Shusen Yang ; McCann, Julie A. ; Jie Lin ; Xinyu Yang
Volume :
53
Issue :
2
fYear :
2015
fDate :
Feb. 2015
Firstpage :
206
Lastpage :
213
Abstract :
Smart grids are essentially electric grids that use information and communication technology to provide reliable, efficient electricity transmission and distribution. Security and trust are of paramount importance. Among various emerging security issues, FDI attacks are one of the most substantial ones, which can significantly increase the cost of the energy distribution process. However, most current research focuses on countermeasures to FDIs for traditional power grids rather smart grid infrastructures. We propose an efficient and real-time scheme to detect FDI attacks in smart grids by exploiting spatial-temporal correlations between grid components. Through realistic simulations based on the US smart grid, we demonstrate that the proposed scheme provides an accurate and reliable solution.
Keywords :
power engineering computing; power system security; security of data; smart power grids; FDI attacks detection; false data injection attacks detection; grid components; smart-grid systems; spatial-temporal correlations; Communication technology; Error analysis; Smart grids; Smart meters; State estimation;
fLanguage :
English
Journal_Title :
Communications Magazine, IEEE
Publisher :
ieee
ISSN :
0163-6804
Type :
jour
DOI :
10.1109/MCOM.2015.7045410
Filename :
7045410
Link To Document :
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