Analysis of Legal Attributes and Rights Attributes of Personal Information from the Perspective of Big Data

With the popularization and rapid development of Internet technology (IT), social activities based on the exchange of personal information are rapidly popularizing. Although the free flow of a huge volume of personal data meets the needs of information exchange, its illicit use poses legal risks to...

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Bibliographic Details
Published inComputational and mathematical methods in medicine Vol. 2022; pp. 9731414 - 10
Main Author Yan, Jingzhong
Format Journal Article
LanguageEnglish
Published United States Hindawi 17.06.2022
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Summary:With the popularization and rapid development of Internet technology (IT), social activities based on the exchange of personal information are rapidly popularizing. Although the free flow of a huge volume of personal data meets the needs of information exchange, its illicit use poses legal risks to rights holders and infringes on the applicable rights and interests of the information subject. The ambiguity of the right attribute and legal attribute of personal information leads to the scattered protection of personal information in the legislative system in different legal norms. Based on this background, this paper constructs an evaluation index based on the legal attributes and rights attributes of personal information rights and proposes a rationality evaluation method for the attributes of personal information rights based on neural networks. The completed work is as follows: (1) focusing on the legal attributes and the right attribute is discussed in detail, and the dissimilar views of scholars at home and abroad are presented. (2) The back propagation neural network (BPNN) model structure required in this study is defined, and the evaluation index based on the legal attribute and right attribute of personal information right is produced. (3) Use big data technology to collect relevant data and compare the results obtained by the BPNN model with the results obtained by the improved BPNN model. The results show that the improved BPNN evaluate model has smaller error and higher accuracy.
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Academic Editor: Naeem Jan
ISSN:1748-670X
1748-6718
DOI:10.1155/2022/9731414