Research Article
On Data Classification and Grading Methods for Petrochemical Enterprises
@INPROCEEDINGS{10.4108/eai.1-9-2023.2338835, author={Pingping Zhao and Tao Zhang and Xiaoman Cheng and Weiqing Huang and Zhiqi He}, title={On Data Classification and Grading Methods for Petrochemical Enterprises}, proceedings={Proceedings of the 2nd International Conference on Public Management, Digital Economy and Internet Technology, ICPDI 2023, September 1--3, 2023, Chongqing, China}, publisher={EAI}, proceedings_a={ICPDI}, year={2023}, month={11}, keywords={petrochemical enterprises; data classification and grading; data security}, doi={10.4108/eai.1-9-2023.2338835} }- Pingping Zhao
Tao Zhang
Xiaoman Cheng
Weiqing Huang
Zhiqi He
Year: 2023
On Data Classification and Grading Methods for Petrochemical Enterprises
ICPDI
EAI
DOI: 10.4108/eai.1-9-2023.2338835
Abstract
Data classification and grading management is crucial for ensuring data security and facilitating rational development and utilization. Petrochemical enterprises, as custodians and processors of data, urgently need to establish a unified and scientific system for safeguarding classified data. This article proposes a hybrid classification approach that considers multiple dimensions such as the origin, business domain, and security attributes of petrochemical enterprise's data to construct a multi-tiered data classification system. By comprehensively considering the objects, the scope and the extent of impact, the petrochemical enterprise's data is graded into four levels based on their varying degrees of sensitivity.
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