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Martinez JfAuthorLópez LAuthor

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March 24, 2021
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A dynamic membership group-based multiple-data aggregation scheme for smart grid

Publicated to: IEEE Internet of Things Journal. 8 (15): 12360-12374 - 2021-08-01 8(15), DOI: 10.1109/JIOT.2021.3063412

Authors:

Chen, YW; Martínez-Ortega, JF; López, L; Yu, HY; Yang, Z
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Affiliations

Beijing Univ Technol, Coll Comp Sci, Beijing Key Lab Trusted Comp, Beijing 10014, Peoples R China - Author
Beijing Univ Technol, Data Min & Secur Lab, Coll Comp Sci, Beijing 10014, Peoples R China - Author
Beijing University of Technology - Author
Escuela Tecnica Superior de Ingenieria y Sistemas de Telecomunicacion, Universidad Politecnica de Madrid - Author
Univ Politecn Madrid, Escuela Tecn Super Ingn Sistemas & Telecomun, Dept Ingn Telemat & Elect, Madrid 28031, Spain - Author
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Abstract

IEEE In the smart grid, meters report their real-time electricity consumption data to a utility supplier, the utility supplier can adjust its supply accordingly. However, adversaries can infer users’ privacy behaviors based on publically transferred real-time electricity consumption data. Data aggregation schemes protect users’ privacy from being leaked. We find two major problems are unsolved: meter failure problem and dynamic membership problem. To solve these problems, we designed a dynamic membership group-based multiple-data aggregation scheme. First, a group-based key establishment scheme is proposed, meters are divided into groups, meters in a group build keys to encrypt their data, the meter failure problem is alleviated. If one group has broken meters, the other groups will not be affected. Second, the dynamic join, dynamic leave, and meter replacement techniques are proposed, dynamic membership is achieved by allowing meters to update their keys. The simulation results show a meter’s computation cost and communication cost are the minima among related works, which makes the proposed scheme more suitable for the IoT scenario. Besides, we designed a data encoding method and data retrieve method, we designed two attacks: ‘bilinear map pairing attack’ and ‘zero attack’.
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Keywords

cryptographydata aggregationdata privacydata securityencodingencryptionprivacyreal-time systemsscalabilitysecuresmart gridsCryptographyData aggregationData privacyData securityEncodingEncryptionFault-toleranceMetersReal-time systemsScalability.Smart grids

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal IEEE Internet of Things Journal due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2021, it was in position 9/164, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Information Systems. Notably, the journal is positioned above the 90th percentile.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 1.17. This indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: ESI Nov 13, 2025)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Weighted Average of Normalized Impact by the Scopus agency: 1.37 (source consulted: FECYT Mar 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2026-04-27, the following number of citations:

  • WoS: 16
  • Scopus: 25
  • Google Scholar: 24
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Impact and social visibility

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/86138/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 125
  • Downloads: 1
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: China.

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