Imperial College London

ProfessorJulieMcCann

Faculty of EngineeringDepartment of Computing

Professor of Computer Systems
 
 
 
//

Contact

 

+44 (0)20 7594 8375j.mccann Website

 
 
//

Location

 

258ACE ExtensionSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Chen:2015:10.1109/MCOM.2015.7045410,
author = {Chen, P-Y and Yang, S and McCann, JA and Lin, J and Yang, X},
doi = {10.1109/MCOM.2015.7045410},
journal = {IEEE Communications Magazine},
pages = {206--213},
title = {Detection of False Data Injection Attacks in Smart-Grid Systems},
url = {http://dx.doi.org/10.1109/MCOM.2015.7045410},
volume = {53},
year = {2015}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - 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.
AU - Chen,P-Y
AU - Yang,S
AU - McCann,JA
AU - Lin,J
AU - Yang,X
DO - 10.1109/MCOM.2015.7045410
EP - 213
PY - 2015///
SN - 1558-1896
SP - 206
TI - Detection of False Data Injection Attacks in Smart-Grid Systems
T2 - IEEE Communications Magazine
UR - http://dx.doi.org/10.1109/MCOM.2015.7045410
UR - http://hdl.handle.net/10044/1/21516
VL - 53
ER -