Survey of Security Advances in Smart Grid: A Data Driven Approach
Abstract
With the integration of advanced computing and communication technologies, smart grid is considered as the next-generation power system, which promises self healing, resilience, sustainability, and efficiency to the energy critical infrastructure. The smart grid innovation brings enormous challenges and initiatives across both industry and academia, in which the security issue emerges to be a critical concern. In this paper, we present a survey of recent security advances in smart grid, by a data driven approach. Compared with existing related works, our survey is centered around the security vulnerabilities and solutions within the entire lifecycle of smart grid data, which are systematically decomposed into four sequential stages: 1) data generation; 2) data acquisition; 3) data storage; and 4) data processing. Moreover, we further review the security analytics in smart grid, which employs data analytics to ensure smart grid security. Finally, an effort to shed light on potential future research concludes this paper.
Recommended Citation
S. Tan et al., "Survey of Security Advances in Smart Grid: A Data Driven Approach," IEEE Communications Surveys and Tutorials, vol. 19, no. 1, pp. 397 - 422, Institute of Electrical and Electronics Engineers (IEEE), Jan 2017.
The definitive version is available at https://doi.org/10.1109/COMST.2016.2616442
Department(s)
Computer Science
Research Center/Lab(s)
Center for High Performance Computing Research
Keywords and Phrases
Data acquisition; Data handling; Digital storage; Electric power transmission networks; Surveying; Surveys; Communication technologies; Data driven; Data-driven approach; Entire life cycles; security; Security Analytics; Security vulnerabilities; Smart grid; Smart power grids; Data-driven
International Standard Serial Number (ISSN)
1553-877X
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2017
Comments
This work was supported by National Science Foundation under Grant NSF-1125165, Grant NSF-1135814, Grant NSF-1303359, Grant NSF-1442630, Grant NSF-1066391, Grant NSFC-61202369, Grant NSF CNS-1545037, and Grant NSF CNS-1545050.