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Black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data

Xueyan Liu,Ruirui Sun,Linpeng Li, Wenjing Li, Tao Liu

KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS(2023)

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Abstract
Epidemiological survey is an important means for the prevention and control of infectious diseases. Due to the particularity of the epidemic survey, 1) epidemiological survey in epidemic prevention and control has a wide range of people involved, a large number of data collected, strong requirements for information disclosure and high timeliness of data processing; 2) the epidemiological survey data need to be disclosed at different institutions and the use of data has different permission requirements. As a result, it easily causes personal privacy disclosure. Therefore, traditional access control technologies are unsuitable for the privacy protection of epidemiological survey data. In view of these situations, we propose a black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data. Firstly, a black box-assisted multi-attribute authority management mechanism without a trusted center is established to avoid authority deception. Meanwhile, the establishment of a master key-free system not only reduces the storage load but also prevents the risk of master key disclosure. Secondly, a sensitivity classification method is proposed according to the confidentiality degree of the institution to which the data belong and the importance of the data properties to set fine-grained access permission. Thirdly, a hierarchical authorization algorithm combined with data sensitivity and hierarchical attribute-based encryption (ABE) technology is proposed to achieve hierarchical access control of epidemiological survey data. Efficiency analysis and experiments show that the scheme meets the security requirements of privacy protection and key management in epidemiological survey.
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Key words
Epidemiological survey, Hierarchical attribute-based encryption, Characteristic value, Multi-authority, Black box
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