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An Efficient Lightweight Authentication Scheme for Smart Meter

Jingqi Du, Chengjing Dai, Pinshang Mao, Wenlong Dong, Xiujun Wang and Zhongwei Li ()
Additional contact information
Jingqi Du: Industrial Control Expansion Department, CLP Great Wall Internet System Application Co., Ltd., Beijing 100088, China
Chengjing Dai: Energy Planning Research Center, China Energy Engineering Group Yunnan Electric Power Design Institute Co., Ltd., Kunming 650051, China
Pinshang Mao: Marketing Center, NR Electric Co., Ltd., Nanjing 210000, China
Wenlong Dong: College of Data Science and Technology, Heilongjiang University, Harbin 150080, China
Xiujun Wang: College of Data Science and Technology, Heilongjiang University, Harbin 150080, China
Zhongwei Li: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China

Mathematics, 2024, vol. 12, issue 8, 1-17

Abstract: With the rapid development of the information age, smart meters play an important role in the smart grid. However, there are more and more attacks on smart meters, which mainly focus on the identity authentication of smart meters and the security protection of electricity consumption data. In this paper, an efficient lightweight smart meter authentication scheme is proposed based on the Chinese Remainder Theorem (CRT), which can realize the revocation of a single smart meter user by publishing a secret random value bound to the smart meter identity. The proposed scheme not only protects the security of smart meter electricity consumption data by using encryption, but also resists identity attacks from both internal and external adversaries by using hash functions and timestamps. Experiment shows that the proposed scheme has lower computation overhead and communication overhead than other authentication schemes and is more suitable for smart meter authentication.

Keywords: smart meters; authentication; Chinese remainder theorem; collusion attack; revocation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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