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| Research on Privacy Data Identification and Measurement Based on Medical Information Text |
| Zhang Kailiang1,2, Zang Guoquan1,2, Xiao Yang1 |
1.School of Information Management, Zhengzhou University, Zhengzhou 450001
2.Research Institute of Data Science, Zhengzhou City, Zhengzhou 450001 |
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Abstract The results of data classification in medical industry standards are fuzzy, with few accompanying measurement results. Considering existing problems, this study adopted medical information text mining to objectively measure medical data privacy. Measurement results can provide a reference for verifying and improving current medical data classification results. In this study, the sources of medically sensitive data included industry standards, legal regulations, academic papers, and breach cases. The medically sensitive data unit is composed of sensitive nouns (also known as sensitive data items), sensitive verbs, and sensitive degree words, which are used in the privacy recognition model. The privacy measurement model considers the sensitivity, semantic strength, and text strength of sensitive data. In ranking the results of privacy values, medical application data ranked the highest, followed by health status, medical payment, and personal attribute data.
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Received: 15 January 2024
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