• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Privacy-preserving Data Aggregation Scheme with Efficient Batch Verification in Smart Grid

Vol. 15, No. 2, February 28, 2021
10.3837/tiis.2021.02.013, Download Paper (Free):

Abstract

This paper presents a privacy-preserving data aggregation scheme deals with the multidimensional data. It is essential that the multidimensional data is rarely mentioned in all researches on smart grid. We use the Paillier Cryptosystem and blinding factor technique to encrypt the multidimensional data as a whole and take advantage of the homomorphic property of the Paillier Cryptosystem to achieve data aggregation. Signature and efficient batch verification have also been applied into our scheme for data integrity and quick verification. And the efficient batch verification only requires 2 pairing operations. Our scheme also supports fault tolerance which means that even some smart meters don’t work, our scheme can still work well. In addition, we give two extensions of our scheme. One is that our scheme can be used to compute a fixed user’s time-of-use electricity bill. The other is that our scheme is able to effectively and quickly deal with the dynamic user situation. In security analysis, we prove the detailed unforgeability and security of batch verification, and briefly introduce other security features. Performance analysis shows that our scheme has lower computational complexity and communication overhead than existing schemes.


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Cite this article

[IEEE Style]
Y. Zhang, J. Chen, H. Zhou and L. Dang, "A Privacy-preserving Data Aggregation Scheme with Efficient Batch Verification in Smart Grid," KSII Transactions on Internet and Information Systems, vol. 15, no. 2, pp. 617-636, 2021. DOI: 10.3837/tiis.2021.02.013.

[ACM Style]
Yueyu Zhang, Jie Chen, Hua Zhou, and Lanjun Dang. 2021. A Privacy-preserving Data Aggregation Scheme with Efficient Batch Verification in Smart Grid. KSII Transactions on Internet and Information Systems, 15, 2, (2021), 617-636. DOI: 10.3837/tiis.2021.02.013.