Skip to main content

ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Smart Grids
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1444505

A Synchronous Compression and Encryption Method for Massive Electricity Consumption Data Privacy Preserving

Provisionally accepted
Ruifeng Zhao Ruifeng Zhao *Jiangang Lu Jiangang Lu Zhiwen Yu Zhiwen Yu Kaiwen Zeng Kaiwen Zeng
  • Guangdong Grid C, Guangzhou, China

The final, formatted version of the article will be published soon.

    The security of user channels and data must be ensured while transmitting electrical usage information in the new power system, making it a challenge to address potential unauthorized data access and the high resource demands of complex encryption systems. This paper addresses privacy in power systems requiring efficient source-load interactions by introducing a novel data compression synchronous encryption algorithm within a compressed sensing framework. Our proposed algorithm uses a ternary Logistic-Tent chaotic system for generating a chaotic measurement matrix, allowing simultaneous data compression and encryption of user-side voltage and current data. This mitigates high-frequency sampling overload and ensures data confidentiality. The implementation of a joint random model at both compression and reconstruction stages eliminates the need for key transmission, reducing management costs and leakage risks. The proposed algorithm was validated using the PLAID dataset, demonstrating that the time required for a single encryption-decryption operation can be reduced by up to 81.99% compared to the asymmetric RSA algorithm. Additionally, compared to the symmetric AES algorithm, the proposed method significantly enhances confidentiality.

    Keywords: electricity consumption information, Privacy preserving, compressed sensing, joint random model, Chaotic system

    Received: 05 Jun 2024; Accepted: 29 Nov 2024.

    Copyright: © 2024 Zhao, Lu, Yu and Zeng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Ruifeng Zhao, Guangdong Grid C, Guangzhou, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.