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Privacy-Preserving Electricity Billing System Using Functional Encryption

Author

Listed:
  • Jong-Hyuk Im

    (Department of Computer Engineering, Inha University, Incheon 22212, Korea)

  • Hee-Yong Kwon

    (Department of Computer Engineering, Inha University, Incheon 22212, Korea)

  • Seong-Yun Jeon

    (Department of Computer Engineering, Inha University, Incheon 22212, Korea)

  • Mun-Kyu Lee

    (Department of Computer Engineering, Inha University, Incheon 22212, Korea)

Abstract

The development of smart meters that can frequently measure and report power consumption has enabledelectricity providers to offer various time-varying rates, including time-of-use and real-time pricing plans. High-resolution power consumption data, however, raise serious privacy concerns because sensitive information regarding an individual’s lifestyle can be revealed by analyzing these data. Although extensive research has been conducted to address these privacy concerns, previous approaches have reduced the quality of measured data. In this paper, we propose a new privacy-preserving electricity billing method that does not sacrifice data quality for privacy. The proposed method is based on the novel use of functional encryption. Experimental results on a prototype system using a real-world smart meter device and data prove the feasibility of the proposed method.

Suggested Citation

  • Jong-Hyuk Im & Hee-Yong Kwon & Seong-Yun Jeon & Mun-Kyu Lee, 2019. "Privacy-Preserving Electricity Billing System Using Functional Encryption," Energies, MDPI, vol. 12(7), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1237-:d:218787
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    Citations

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    Cited by:

    1. Marta Moure-Garrido & Celeste Campo & Carlos Garcia-Rubio, 2022. "Entropy-Based Anomaly Detection in Household Electricity Consumption," Energies, MDPI, vol. 15(5), pages 1-21, March.

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