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SEMDA: Secure and Efficient Multidimensional Data Aggregation in Smart Grid without a Trusted Third Party.

Authors :
Song, Zichao
Zhong, Weidong
Zhou, Tanping
Chen, Dong
Ding, Yujie
Yang, Xiaoyuan
Source :
Security & Communication Networks; 2/1/2023, p1-13, 13p
Publication Year :
2023

Abstract

Smart grids are a combination of traditional power system engineering as well as information and communications technology. Smart grid terminals provide convenient services to users by aggregating their data in real time. However, terminals can derive user privacy information from real-time data on smart devices. Therefore, security data aggregation has been widely studied in the field of smart grid. Most existing schemes are one-dimensional data aggregation or rely on a trusted third party. In reality, multidimensional data (such as a user's electricity consumption or user's main usage time, etc.) makes sense for terminals to flexibly adjust supply and demand strategies. In this paper, we propose an efficient and secure multidimensional data aggregation scheme that supports batch validation without a trusted third party. Firstly, we apply the Chinese remainder theorem to encode the user's multidimensional data and realize the independence of each dimension in terminal decryption. Secondly, we adopt a secure key negotiation protocol that does not require a trusted third party. Finally, based on paillier homomorphic encryption and bilinear pairing, we construct an encryption scheme that can reuse the key and blind factor and support batch verification. The analysis results show that our scheme is secure for users' privacy protection. Experimental results show that, compared with existing 1 dimensional aggregation schemes, our scheme has almost no growth in computational overhead for terminal decryption. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19390114
Database :
Complementary Index
Journal :
Security & Communication Networks
Publication Type :
Academic Journal
Accession number :
161621337
Full Text :
https://doi.org/10.1155/2023/6693296