Toward Data Integrity Attacks Against Optimal Power Flow in Smart Grid

In this paper, we address the security issue of optimal power flow (OPF) (as a key component in the smart grid). To be specific, we investigate the data integrity attack against OPF with the least effort from the adversary's perspective, and propose effectively defense schemes to combat the dat...

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Veröffentlicht in:IEEE internet of things journal 2017-10, Vol.4 (5), p.1726-1738
Hauptverfasser: Yang, Qingyu, Li, Donghe, Yu, Wei, Liu, Yuanke, An, Dou, Yang, Xinyu, Lin, Jie
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Sprache:eng
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Zusammenfassung:In this paper, we address the security issue of optimal power flow (OPF) (as a key component in the smart grid). To be specific, we investigate the data integrity attack against OPF with the least effort from the adversary's perspective, and propose effectively defense schemes to combat the data integrity attack, with respect to the number of nodes to compromise and the amount of information to manipulate. The investigated attack can first select the minimum number of target nodes to compromise by analyzing the difference between the capacity of transmission line and the real transmission power, and then search for a critical attack vector as an optimal attack strategy. To defend against such an attack, we develop the defensive schemes by not only protecting the critical nodes but also detecting the existence of attacks based on false measurement detection schemes. Based on various IEEE standard systems, we show the effectiveness of our investigated attack scheme and the corresponding defense schemes. The experimental results show that the discovered compromised nodes and critical attack vector could lead to the increase of the fuel cost from the power generation by compromising the least number of nodes and injecting the least amount of false information, in comparison with the random attack as the baseline attack strategy. In addition, our two developed defensive schemes are capable of making OPF resilient to the data integrity attack via protecting critical nodes and identifying the falsified measurements accurately in the system.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2017.2709252