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Chen, Yuwen, Fernán Martínez, José, Castillejo Parrilla, Pedro ORCID: https://orcid.org/0000-0001-7356-717X and López Santidrián, Lourdes
(2018).
A Privacy-Preserving Noise Addition Data Aggregation Scheme for Smart Grid.
"Energies", v. 11
(n. 11);
pp. 1-17.
ISSN 1996-1073.
https://doi.org/10.3390/en11112972.
Title: | A Privacy-Preserving Noise Addition Data Aggregation Scheme for Smart Grid |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | Energies |
Date: | November 2018 |
ISSN: | 1996-1073 |
Volume: | 11 |
Subjects: | |
Freetext Keywords: | noise generation methods; bilinear map; smart grid; meter aggregation; homomorphic encryption |
Faculty: | E.T.S.I. y Sistemas de Telecomunicación (UPM) |
Department: | Ingeniería Telemática y Electrónica |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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Smart meters are applied to the smart grid to report instant electricity consumption to servers periodically; these data enable a fine-grained energy supply. However, these regularly reported data may cause some privacy problems. For example, they can reveal whether the house owner is at home, if the television is working, etc. As privacy is becoming a big issue, people are reluctant to disclose this kind of personal information. In this study, we analyzed past studies and found that the traditional method suffers from a meter failure problem and a meter replacement problem, thus we propose a smart meter aggregation scheme based on a noise addition method and the homomorphic encryption algorithm, which can avoid the aforementioned problems. After simulation, the experimental results show that the computation cost on both the aggregator and smart meter side is reduced. A formal security analysis shows that the proposed scheme has semantic security.
Item ID: | 55491 |
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DC Identifier: | https://oa.upm.es/55491/ |
OAI Identifier: | oai:oa.upm.es:55491 |
DOI: | 10.3390/en11112972 |
Official URL: | https://www.mdpi.com/1996-1073/11/11/2972 |
Deposited by: | Memoria Investigacion |
Deposited on: | 17 Jan 2020 12:35 |
Last Modified: | 17 Jan 2020 12:35 |