Efficient and privacy-preserving certificateless data aggregation in Internet of things–enabled smart grid

Aijing Sun, Axin Wu, Xiaokun Zheng and Fangyuan Ren

International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 4, 1550147719842062

Abstract: As a typical and promising application of the Internet of things, smart grid will play an increasingly important role in the future power system. However, security and privacy issues in smart grids need to be addressed. If the user’s electricity consumption is transmitted in plaintext, the data may be used by some illegal users. At the same time, malicious users may send false data such that the control center makes a wrong power resource scheduling. In addition, efficiency issues should be taken into account in Internet of things applications. To overcome these challenges, an efficient and privacy-preserving certificateless data aggregation scheme is proposed for Internet of things–enabled smart grids. The confidentiality and integrity of data can be guaranteed, and the identity of users can be hidden in our scheme. In particular, if some users have malicious behaviors, they will be tracked. The proposed scheme can resist replay attacks, modification attacks, and impersonation attacks. In the process of collecting data, computation of encryption and signature generation do not need expensive bilinear pairings. Furthermore, batch verification is used to improve efficiency of verification. It is demonstrated that the security, privacy, and efficiency issues in smart grid are addressed based on security and performance analysis.

Keywords: Internet of things; smart grid; data aggregation; batch verification; privacy (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:4:p:1550147719842062

DOI: 10.1177/1550147719842062

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