Abstract
It is well-known that critical infrastructures would be targets for cyber attacks. In this paper, we focus on smart grids. In a smart grid system, information from smart meters would be used to perform a state estimation in real time in order to maintain the stability of the system. A wrong estimation can lead to diastrous consequences (e.g. suspension of electricity supply or a big financial loss). Unfortunately, quite a number of recent results showed that attacks on this estimation process are feasible by manipulating readings of only a few meters. In this paper, we focus on nonlinear state estimation which is a more realistic model and widely employed in a real smart grid environment. We summarize and categorize all possible attacks, and review the mechanisms behind. We also briefly talk about the countermeasures. We hope that the community would be able to come up with a better protection scheme for smart grids.
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Notes
- 1.
As given in Table 2, \(P_j\) and \(Q_j\) refer to the real power injection and reactive power injection on bus j.
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Acknowledgments
The work described in this paper was partially supported by the HKU Seed Fundings for Applied Research 201409160030; HKU Seed Fundings for Basic Research 201311159149 and 201411159122; National Natural Science Foundation of China (61572157, 61401176, 61402136), PRC; Shenzhen Strategic Emerging Industry Development Foundation (JCYJ2015040316 1923509 and JCYJ20150617155357681), PRC, National High Technology Research and Development Program of China (2015AA016008), Projects of International Cooperation and Exchanges NSFC (61361166006), China, NSFCRGC Joint Research Scheme (N_HKU 72913), Hong Kong, Natural Science Foundation of Guangdong Province, China (2014A030310205, 2014A030313697), and Excellent Young Teachers Program of Guangdong High Education, China (YQ2015018), and China State Scholarship Fund.
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Wang, J., Hui, L.C.K., Yiu, S.M., Cui, X., Ke Wang, E., Fang, J. (2016). A Survey on the Cyber Attacks Against Non-linear State Estimation in Smart Grids. In: Liu, J., Steinfeld, R. (eds) Information Security and Privacy. ACISP 2016. Lecture Notes in Computer Science(), vol 9722. Springer, Cham. https://doi.org/10.1007/978-3-319-40253-6_3
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DOI: https://doi.org/10.1007/978-3-319-40253-6_3
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