2021•2021 6th International Conference on Power and Renewable Energy (ICPRE)Requires access

Differential Privacy Algorithm for Integrated Energy System Based on Improved K-means

Zhengquan Lv, Liang Wei, Yijun Chen, Yuan Liu, Chaoyang Li, Daogang Peng

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Abstract

This paper studies the privacy protection method of k-means clustering integrated energy system based on improved differential privacy protection. Firstly, it introduces the research status of integrated energy system and privacy protection, and the basic principles and methods of differential privacy protection. In order to solve the problem that the reliability and concealment of clustering results of k-means clustering method can not be taken into account, a new differential privacy k-means clustering method is proposed, and it is proved that it satisfies differential privacy protection. Finally, the experiment proves that the improved differential privacy protection k-means clustering integrated energy system privacy protection method can protect data privacy and improve the stability of clustering effect, which greatly improves the data privacy protection of integrated energy system.

About this research paper

What this paper is about

This paper studies the privacy protection method of k-means clustering integrated energy system based on improved differential privacy protection. Firstly, it introduces the research status of integrated energy system and privacy protection, and the basic principles and methods of differential privacy protection. In order to solve the problem that the reliability and concealment of clustering results of k-means clustering method can not be taken into account, a new differential privacy k-means clustering method is proposed, and it is proved that it satisfies differential privacy protection. Finally, the experiment proves that the improved differential privacy protection k-means clustering integrated energy system privacy protection method can protect data privacy and improve the stability of clustering effect, which greatly improves the data privacy protection of integrated energy system.

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Available abstract

This paper studies the privacy protection method of k-means clustering integrated energy system based on improved differential privacy protection. Firstly, it introduces the research status of integrated energy system and privacy protection, and the basic principles and methods of differential privacy protection. In order to solve the problem that the reliability and concealment of clustering results of k-means clustering method can not be taken into account, a new differential privacy k-means clustering method is proposed, and it is proved that it satisfies differential privacy protection. Finally, the experiment proves that the improved differential privacy protection k-means clustering integrated energy system privacy protection method can protect data privacy and improve the stability of clustering effect, which greatly improves the data privacy protection of integrated energy system.

Key concepts: Differential privacy, Cluster analysis, Privacy protection, Computer science, Reliability (semiconductor), Data mining, Information privacy, Data Protection Act 1998

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