Statistical structure learning of smart grid for detection of false data injection

Author(s):  
Hanie Sedghi ◽  
Edmond Jonckheere
Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1153
Author(s):  
Francesco Liberati ◽  
Emanuele Garone ◽  
Alessandro Di Giorgio

This paper presents a review of technical works in the field of cyber-physical attacks on the smart grid. The paper starts by discussing two reference mathematical frameworks proposed in the literature to model a smart grid under attack. Then, a review of cyber-physical attacks on the smart grid is presented, starting from works on false data injection attacks against state estimation. The aim is to present a systematic and quantitative discussion of the basic working principles of the attacks, also in terms of the inner smart grid vulnerabilities and dynamical properties exploited by the attack. The main contribution of the paper is the attempt to provide a unifying view, highlighting the fundamental aspects and the common working principles shared by the attack models, even when targeting different subsystems of the smart grid.


Author(s):  
Mohammad Ashrafuzzaman ◽  
Saikat Das ◽  
Ananth A. Jillepalli ◽  
Yacine Chakhchoukh ◽  
Frederick T. Sheldon

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 15499-15509
Author(s):  
Chao Pei ◽  
Yang Xiao ◽  
Wei Liang ◽  
Xiaojia Han

2014 ◽  
Vol 27 (3) ◽  
pp. 1457-1467 ◽  
Author(s):  
Hossein Hosseini ◽  
Seyed Mohamad Taghi Bathaee ◽  
Ali Abedini ◽  
Majid Hosseina ◽  
Alireza Fereidunain

2021 ◽  
Author(s):  
Zheng Xu ◽  
Qiang Ma ◽  
Lin Lin ◽  
Qi-Gui Nie ◽  
Xin Liu ◽  
...  

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