Author:
Zhang Qianyi,Zhang Chi,Ni Jiaming,Wang Xuqiang,Zhang Yao
Abstract
Abstract
For the problems of privacy data protection caused by massive data sharing in the construction of power Internet of things, a data sensitivity measurement and classification model based on information entropy and BP neural network is proposed. Firstly, a recognition matching algorithm is proposed to identify the sensitive level of attributes in the dataset, and the information entropy is used to determine the weight of attributes sensitivity level, so as to calculate the sensitivity measurement value of records in the dataset; finally, the BP neural network is used to output the data classification results. The experimental results show that the model can achieve accurate measurement and classification of data, with low incorrect judgment rate and error rate.
Subject
General Physics and Astronomy
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