Data Privacy Protection Methods for Electric Power IoT

The electric power Internet of Things (IoT) contains a vast amount of sensitive data. The surge in data volume and diversification of applications pose security risks during data transmission and storage, making it crucial for users to protect the privacy of these data. This paper proposes a data privacy protection method for the IoT based on trusted identity verification. By utilizing trusted identity verification technology to generate an encrypted database, the IoT data is preprocessed. This data is then used to construct a data privacy encryption model, ultimately achieving privacy protection for IoT data. Simulation experiments have verified that the proposed data privacy protection method for the IoT can effectively protect the privacy of IoT data and store it to the greatest extent, with a storage capacity far exceeding other commonly used methods and a low data leakage rate.

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Publication Details

Published
2025-04-11
DOI
https://doi.org/10.1109/ainit65432.2025.11035051
Primary Topic
Technology and Data Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Data Privacy Protection Methods for Electric Power IoT

Xuening Zhang, Kaili Zhao, H. R. Qin, Jie Bai et al.
Technology and Data Analysis
article

Data Privacy Protection Methods for Electric Power IoT

Xuening Zhang, Kaili Zhao, H. R. Qin, Jie Bai, Jing Wang, Weiwei Fu, G. Zhao
article en

Abstract

The electric power Internet of Things (IoT) contains a vast amount of sensitive data. The surge in data volume and diversification of applications pose security risks during data transmission and storage, making it crucial for users to protect the privacy of these data. This paper proposes a data privacy protection method for the IoT based on trusted identity verification. By utilizing trusted identity verification technology to generate an encrypted database, the IoT data is preprocessed. This data is then used to construct a data privacy encryption model, ultimately achieving privacy protection for IoT data. Simulation experiments have verified that the proposed data privacy protection method for the IoT can effectively protect the privacy of IoT data and store it to the greatest extent, with a storage capacity far exceeding other commonly used methods and a low data leakage rate.

Affordable and clean energy
Openalex Percentile: Top 79%
Technology and Data Analysis
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Data Privacy Protection Methods for Electric Power IoT — Xuening Zhang, Kaili Zhao, et al. · (2025) | TGRS Research Map | TGRS