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A fine-grained privacy protection data aggregation scheme for outsourcing smart grid

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Abstract

Compared with the traditional power grid, smart grid involves many advanced technologies and applications. However, due to the rapid development of various network technologies, smart grid is facing the challenges of balancing privacy, security, efficiency, and functionality. In the proposed scheme, we design a privacy protection scheme for outsourcing smart grid aided by fog computing, which supports fine-grained privacy-protected data aggregation based on user characteristics. The fog server matches the encrypted characteristics in the received message with the encrypted aggregation rules issued by the service provider. Therefore, the service provider can get more fine-grained analysis data based on user characteristics. Different from the existing outsourcing smart grid schemes, the proposed scheme can achieve real-time pricing on the premise of protecting user privacy and achieving system fault tolerance. Finally, experiment analyses demonstrate that the proposed scheme has less computation overhead and lower transmission delay than existing schemes.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Grant Nos. 62125205, 62072361 and 61872449).

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Authors and Affiliations

  1. School of Cyber Engineering, Xidian University, Xi’an, 710071, China

    Hongyang Li & Xinghua Li

  2. Strategic Support Force Information Engineering University, Zhengzhou, 450001, China

    Qingfeng Cheng

Authors
  1. Hongyang Li
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  2. Xinghua Li
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  3. Qingfeng Cheng
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Corresponding author

Correspondence to Qingfeng Cheng.

Additional information

Hongyang Li received the BS degree in computer science and technology from Changchun University of Science, China in 2019. He is currently working toward the MS degree in security of cyberspace in Xidian University, China. His research interests are mainly in edge computing, date aggregation and information security.

Xinghua Li received the ME and PhD degrees in computer science from Xidian University, China in 2004 and 2007, respectively. He is currently a professor in the School of Cyber Engineering, Xidian University, China. His research interests include wireless networks security, privacy protection, cloud computing, and security protocol formal methodology. He is a member of the IEEE.

Qingfeng Cheng received the MS degree in mathematics from National University of Defense Technology, China in 2004 and PhD degree in mathematics from Information Engineering University, China in 2011. He is now a professor in the State Key Laboratory of Mathematical Engineering and Advanced Computing, China. His research interests include cryptography and information security.

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Li, H., Li, X. & Cheng, Q. A fine-grained privacy protection data aggregation scheme for outsourcing smart grid. Front. Comput. Sci. 17, 173806 (2023). https://doi.org/10.1007/s11704-022-2003-y

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