Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19–21, 2023, Hangzhou, China

Research Article

A Method for Assessing the Security of Energy Trading Data Based on Big Data and the Pagerank Algorithm

Download265 downloads
  • @INPROCEEDINGS{10.4108/eai.19-5-2023.2334237,
        author={Weibin  Ding and Deqi  Zhang and Junjia  Yang and Yanzuo  Chen},
        title={A Method for Assessing the Security of Energy Trading Data Based on Big Data and the Pagerank Algorithm},
        proceedings={Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19--21, 2023, Hangzhou, China},
        publisher={EAI},
        proceedings_a={ICBBEM},
        year={2023},
        month={7},
        keywords={energy transaction data; security assessment; big data; pagerank algorithm; assessment methods},
        doi={10.4108/eai.19-5-2023.2334237}
    }
    
  • Weibin Ding
    Deqi Zhang
    Junjia Yang
    Yanzuo Chen
    Year: 2023
    A Method for Assessing the Security of Energy Trading Data Based on Big Data and the Pagerank Algorithm
    ICBBEM
    EAI
    DOI: 10.4108/eai.19-5-2023.2334237
Weibin Ding1,*, Deqi Zhang1, Junjia Yang1, Yanzuo Chen2
  • 1: State Grid Zhejiang Electric Power CO., LTD.
  • 2: State Grid Zhejiang Economic Research Institute
*Contact email: 277322541@qq.com

Abstract

The current assessment of the security of energy transaction data has vague evaluation dimensions, resulting in large errors in the assessment results. To this end, we propose a method for assessing the security of energy transaction data based on big data and the Pagerank algorithm. Determine assessment requirements based on big data and obtain assessment requirements based on six dimensions. Construct a security assessment model and calculate the indicator weights for this model. The assessment results are obtained dynamically based on the Pagerank algorithm. Experiments show that the evaluation results of the method have a small error, with an average error of only 0.22%, which has a high application value.