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Efficient and Privacy-Preserving Data Aggregation Scheme for Smart Grid against Internal Adversaries
Wuhan University, Wuhan, China.
Thapar University, Patiala, India.
University of the District of Columbia, Lexington, Kentucky, USA.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).ORCID iD: 0000-0003-4894-4134
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2017 (English)In: IEEE Transactions on Smart Grid, ISSN 1949-3053, E-ISSN 1949-3061, Vol. 8, no 5, p. 2411-2419Article in journal (Refereed) Published
Abstract [en]

Privacy-Preserving Data Aggregation (P2DA) is an important basic building block that can protect consumer’s privacy in the smart grid environment because it could be used to prevent the extraction of the electricity consumption information of a specific consumer. Due to this important function, the P2DA scheme for the smart grid has attracted a lot of attention from both academic and industry researchers who have proposed many P2DA schemes for the smart grid in recent years. However, most of these P2DA schemes are not secure against internal attackers or cannot provide data integrity. Besides, their computation costs are not satisfactory because the bilinear pairing operation or the hash-to-point operation is performed at the smart meter’s side. To address the deficiencies of previous schemes, we propose a new P2DA scheme against internal attackers using Boneh-Goh-Nissim public key cryptography. The proposed P2DA scheme does not use bilinear pairing or hash-to-point operations making it more computationally efficient than previous P2DA schemes. We also show that the proposed P2DA scheme is provably secure and can meet various security requirements. © Copyright 2017 IEEE

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2017. Vol. 8, no 5, p. 2411-2419
Keywords [en]
smart grid, data aggregation, privacy, security
National Category
Communication Systems Telecommunications
Identifiers
URN: urn:nbn:se:hh:diva-34693DOI: 10.1109/TSG.2017.2720159ISI: 000408221000036Scopus ID: 2-s2.0-85023781439OAI: oai:DiVA.org:hh-34693DiVA, id: diva2:1130390
Available from: 2017-08-09 Created: 2017-08-09 Last updated: 2017-11-29Bibliographically approved

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Vinel, Alexey

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