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