BPRM: Blockchain-Based Privacy Preserving and Robust Data Aggregation Supporting Multifunctionality for Fog-Assisted Smart Grid

While the collection of users’ live or periodic electricity consumption data brings significant advantages for the operation of smart grids, it also heightens the risk of user privacy leakage. Numerous data aggregation schemes have been proposed to address this issue. However, most of these schemes either fail to accommodate the need for multifunctional data analysis or rely on a trusted third party (TTP). Given the efficient data processing capabilities offered by fog computing, we propose a blockchain-based privacy-preserving data aggregation (BPRM) scheme supporting multifunctionality for fog-assisted smart grid without TTP. This scheme ensures data confidentiality and data integrity while providing various statistical functions. In addition, we implement a consensus mechanism between smart meters, further enhancing the security and robustness of the smart grid system. Moreover, not only does the proposed the batch verification reduce the authentication costs but also support error detection in signatures. With BPRM, data center can calculate multiple statistical functions, achieving a win-win strategy. Extensive security and performance analyses demonstrate that BPRM can withstand various security threats and effectively protect user privacy while maintaining efficiency in both computational and communication overhead.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-12-23
DOI
https://doi.org/10.1109/jiot.2024.3521370
Citations
11
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
8.57

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article

BPRM: Blockchain-Based Privacy Preserving and Robust Data Aggregation Supporting Multifunctionality for Fog-Assisted Smart Grid

Chunhua Zhao, Kai Zhang, Zhiquan Liu, Liangliang Wang et al.
11 citations
IEEE Internet of Things Journal
Blockchain Technology Applications and Security
8.57
article

BPRM: Blockchain-Based Privacy Preserving and Robust Data Aggregation Supporting Multifunctionality for Fog-Assisted Smart Grid

Chunhua Zhao, Kai Zhang, Zhiquan Liu, Liangliang Wang, Libo Wang, Kefei Chen, Weiwei Li
article en
11 citations

Abstract

While the collection of users’ live or periodic electricity consumption data brings significant advantages for the operation of smart grids, it also heightens the risk of user privacy leakage. Numerous data aggregation schemes have been proposed to address this issue. However, most of these schemes either fail to accommodate the need for multifunctional data analysis or rely on a trusted third party (TTP). Given the efficient data processing capabilities offered by fog computing, we propose a blockchain-based privacy-preserving data aggregation (BPRM) scheme supporting multifunctionality for fog-assisted smart grid without TTP. This scheme ensures data confidentiality and data integrity while providing various statistical functions. In addition, we implement a consensus mechanism between smart meters, further enhancing the security and robustness of the smart grid system. Moreover, not only does the proposed the batch verification reduce the authentication costs but also support error detection in signatures. With BPRM, data center can calculate multiple statistical functions, achieving a win-win strategy. Extensive security and performance analyses demonstrate that BPRM can withstand various security threats and effectively protect user privacy while maintaining efficiency in both computational and communication overhead.

IEEE Internet of Things JournalVol. 12(9)
Jinan University (CN), Hangzhou Normal University (CN), Hainan University (CN), Shanghai University of Electric Power (CN)
National Natural Science Foundation of China, Shanghai Rising-Star Program
Openalex Percentile: Top 2%
Blockchain Technology Applications and Security
8.57
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