An investigation into personal data sensitivity in the Internet of Everything—insights from China

Weidong Li, Yalin Qin, Changjie Chen and Meng Wang ()
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Weidong Li: Huazhong University of Science and Technology
Yalin Qin: Huazhong University of Science and Technology
Changjie Chen: Huazhong University of Science and Technology
Meng Wang: Huazhong University of Science and Technology

Palgrave Communications, 2025, vol. 12, issue 1, 1-14

Abstract: Abstract The ubiquitous monitoring and collection capabilities of the IoE, as well as its innovative scenarios, have led to changes in the content and type of personal data. Personal data sensitivity, as a standard for measuring privacy attitudes, can provide a reference for the design and improvement of privacy systems. This study aims to evaluate individuals’ personal data sensitivity in the IoE context, to better understand individuals’ current privacy attitudes. This study uses a questionnaire survey to study personal data sensitivity and the antecedents affecting personal data sensitivity among 1921 Chinese citizens. Research suggests that, within the spectrum of 41 personal data categories, identifiers such as ID numbers and home addresses are deemed highly sensitive. Furthermore, within the IoE context, emerging types of personal data, including behavioural and facial recognition data, also demonstrate significant sensitivity. With respect to sensitivity levels, personal data can be categorized into four tiers: very highly sensitive data, highly sensitive data, medium sensitive data, and low sensitive data. The study also finds that perceived privacy risks, privacy concerns, and social influences have a significant impact on personal data sensitivity, and there are differences in public perception of personal data sensitivity among different genders, ages, and educational levels.

Date: 2025
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DOI: 10.1057/s41599-025-04580-x

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