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High Impact False Data Injection Attack against Real-time Pricing in Smart Grids

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Dayaratne, Thusitha
Rudolph, Carsten
Liebman, Ariel
Salehi, Mahsa
He, Shan

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Institute of Electrical and Electronics Engineers Inc.

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The emerging proliferation of information and communication technology throughout the electricity grid enables technologies, such as Demand Response (DR) schemes, eventually creating a Smart Grid. This development is expected to produce effective DR systems where consumers get reduced electricity costs while their utility companies reduce their costs of services due to peak demand reductions with increasing efficiency. False data injection/data integrity attacks on these systems can potentially result in sub-optimal solutions for a majority of users while a potentially malicious subset of users receives benefits. Furthermore, such attacks might also affect the resilience of the Smart Grid. In this paper, we depicted a novel high impact FDIA and evaluate how an adversary can use a targeted strategic data integrity attack in order to get financial benefits through a realtime based pricing scheme. Our experimental results show how a small percentage of overall demand increase can lead to a significant cost reduction for the adversary. Based on our results we elaborate on the significance of this type of false data injection attacks on general distributed DR schemes.

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Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019

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