Sequential cyber-attack detection in the large-scale smart grid system

Author(s):  
Shang Li ◽  
Yasin Yilmaz ◽  
Xiaodong Wang
Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1218
Author(s):  
Tan Duy Le ◽  
Adnan Anwar ◽  
Seng W. Loke ◽  
Razvan Beuran ◽  
Yasuo Tan

The smart grid system is one of the key infrastructures required to sustain our future society. It is a complex system that comprises two independent parts: power grids and communication networks. There have been several cyber attacks on smart grid systems in recent years that have caused significant consequences. Therefore, cybersecurity training specific to the smart grid system is essential in order to handle these security issues adequately. Unfortunately, concepts related to automation, ICT, smart grids, and other physical sectors are typically not covered by conventional training and education methods. These cybersecurity experiences can be achieved by conducting training using a smart grid co-simulation, which is the integration of at least two simulation models. However, there has been little effort to research attack simulation tools for smart grids. In this research, we first review the existing research in the field, and then propose a smart grid attack co-simulation framework called GridAttackSim based on the combination of GridLAB-D, ns-3, and FNCS. The proposed architecture allows us to simulate smart grid infrastructure features with various cybersecurity attacks and then visualize their consequences automatically. Furthermore, the simulator not only features a set of built-in attack profiles but also enables scientists and electric utilities interested in improving smart grid security to design new ones. Case studies were conducted to validate the key functionalities of the proposed framework. The simulation results are supported by relevant works in the field, and the system can potentially be deployed for cybersecurity training and research.


2021 ◽  
Vol 8 ◽  
Author(s):  
Ayush Sinha ◽  
Manasi Mohandas ◽  
Pankaj Pandey ◽  
O. P. Vyas

Cyber-Physical Systems (CPS) is the amalgamation of highly sophisticated sensors with physical spaces. These close conjunctions of sensors with communication infrastructure intrinsically linking to society’s Critical Infrastructures (C.I.) are being witnessed more often in the context of Smart Grid (SG). As a backbone of C.I., Smart Grid demonstrates ability to precisely monitor large scale energy systems and designed in order to achieve complex local and global objectives. Being capable of performing such sophisticated operation it also bears the vulnerability of being exposed for cyber-physical co-ordinated attack that may lead to catastrophic effect. Many researchers have analyze the different stages of cyber-physical co-ordinated attacks like attack detection, prevention, impact analysis and recovery plans but there exist a research gap to address all the issues under single framework. Through this paper, we propose a novel Cyber Physical Defense Framework (CPDF) based on National Institute of Standards and Technology (NIST) guidelines to address the cyber attack on SG. Our work addresses the pre and post attack scenario, attack vector formulation through hierarchical PetriNet modeling and recovery mechanism. We have performed experiment for Distributed Denial of Service (DDoS) and False Data Injection attack (FDI) to validate our framework effectiveness and established the efficacy of proposed model. In the end, we have presented a case study of FDI attack detection using machine learning technique on IEEE 9-bus and 14-bus system.


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