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Open AccessArticle

Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks

1
Department of Electrical Engineering, University of Brasília, Brasília 70910-900, Brazil
2
Brazilian Electricity Regulatory Agency, ANEEL, Brasília 70830-110, Brazil.
3
Elektronische Fahrwerksysteme GmbH, 85080 Ingolstadt, Germany
4
Institute for Information Technology, Ilmenau University of Technology, 98693 Ilmenau, Germany
5
Fraunhofer Institute for Integrated Circuits IIS, 98693 Ilmenau, Germany;
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(5), 1337; https://doi.org/10.3390/s20051337
Received: 8 December 2019 / Revised: 18 February 2020 / Accepted: 20 February 2020 / Published: 29 February 2020
Due to the drastic increase of electricity prosumers, i.e., energy consumers that are also producers, smart grids have become a key solution for electricity infrastructure. In smart grids, one of the most crucial requirements is the privacy of the final users. The vast majority of the literature addresses the privacy issue by providing ways of hiding user’s electricity consumption. However, open issues in the literature related to the privacy of the electricity producers still remain. In this paper, we propose a framework that preserves the secrecy of prosumers’ identities and provides protection against the traffic analysis attack in a competitive market for energy trade in a Neighborhood Area Network (NAN). In addition, the amount of bidders and of successful bids are hidden from malicious attackers by our framework. Due to the need for small data throughput for the bidders, the communication links of our framework are based on a proprietary communication system. Still, in terms of data security, we adopt the Advanced Encryption Standard (AES) 128 bit with Exclusive-OR (XOR) keys due to their reduced computational complexity, allowing fast processing. Our framework outperforms the state-of-the-art solutions in terms of privacy protection and trading flexibility in a prosumer-to-prosumer design. View Full-Text
Keywords: smart grid privacy; energy trade; traffic analysis attack; cryptography smart grid privacy; energy trade; traffic analysis attack; cryptography
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MDPI and ACS Style

Junior, J.M.; da Costa, J.P.C.L.; Garcez, C.C.R.; de Oliveira Albuquerque, R.; Arancibia, A.; Weichenberger, L.; de Mendonça, F.L.L.; Galdo, G.d.; de Sousa Jr., R.T. Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks. Sensors 2020, 20, 1337. https://doi.org/10.3390/s20051337

AMA Style

Junior JM, da Costa JPCL, Garcez CCR, de Oliveira Albuquerque R, Arancibia A, Weichenberger L, de Mendonça FLL, Galdo Gd, de Sousa Jr. RT. Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks. Sensors. 2020; 20(5):1337. https://doi.org/10.3390/s20051337

Chicago/Turabian Style

Junior, Jayme M.; da Costa, João P.C.L.; Garcez, Caio C.R.; de Oliveira Albuquerque, Robson; Arancibia, Arnaldo; Weichenberger, Lothar; de Mendonça, Fábio L.L.; Galdo, Giovanni d.; de Sousa Jr., Rafael T. 2020. "Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks" Sensors 20, no. 5: 1337. https://doi.org/10.3390/s20051337

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