Data Privacy Protection Methods for Electric Power IoT
Xuening Zhang, Kaili Zhao, Xuening Zhang, Haoran Qin, Jie Bai, Weiwei Fu, Jing Wang, Guopeng Zhao · 2025
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.