ISSN: 2245-4578 (Online Version) ISSN:2245-1439 (Print Version)
Multi-Heterogeneous Power Data Security Protection in Smart Grid Based on Data Aggregation and Paillier Homomorphic Encryption Algorithm
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Keywords

Smart grid
data aggregation
Paillier homomorphic encryption
multivariate heterogeneous data
security protection
computational overhead

How to Cite

[1]
B. . Yan, Z. . Zhou, Y. . Fu, and Y. . Su, “Multi-Heterogeneous Power Data Security Protection in Smart Grid Based on Data Aggregation and Paillier Homomorphic Encryption Algorithm”, JCSANDM, vol. 15, no. 04, pp. 1087–1132, Aug. 2026.

Abstract

Multi-heterogeneous power data in smart grid refers to power data that includes multiple types, modalities, and sampling frequencies, such as user electricity consumption, equipment operation, and grid scheduling. The diverse and heterogeneous power data in the smart grid is related to the stable operation of the grid and user privacy. Without effective protection, it is easy to cause risks such as information leakage and scheduling failure. Therefore, targeted security protection solutions need to be constructed. However, there are problems with the loss of information granularity, high risk of privacy leakage, and limited data analysis in the current smart grid power data aggregation and sharing. To enhance the security protection effect of power data, a multi-dimensional data security protection scheme based on data aggregation and Paillier homomorphic encryption is proposed. Firstly, a three-tier system model for multivariate heterogeneous power data in smart grids is constructed (smart meters, data collection stations, and blockchain nodes). Subsequently, the Paillier homomorphic encryption algorithm is integrated to encrypt and aggregate users’ multi-dimensional electricity consumption data. At the same time, data aggregation and consortium chain technology have been introduced. Experimental results demonstrate that this scheme offers significant advantages over traditional Rivest-Shamir-Adleman (RSA) encryption schemes, traditional Advanced Encryption Standard (AES) encryption schemes, Elgamel encryption schemes, and traditional Transmission Control Protocol/Message Queuing Telemetry Transmission Protocol transmission schemes in terms of computational and communication overhead. When the number of users reaches 5000, the computational overhead at data collection stations is only 35.6% of that in traditional RSA methods, and the communication overhead is merely 28.7% of traditional transmission control protocol methods. Additionally, when transmitting power data from 5000 users simultaneously, the information accuracy rate exceeds 92%, and the packet loss rate remains below 0.5%. In conclusion, the proposed scheme provides an efficient and reliable technical pathway for the secure transmission of multivariate heterogeneous power data in smart grids.

https://doi.org/10.13052/jcsm2245-1439.15411
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