Vol. 17, No. 9, September 30, 2023
10.3837/tiis.2023.09.013,
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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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Cite this article
[IEEE Style]
X. Liu, R. Sun, L. Li, W. Li, T. Liu, "Black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data," KSII Transactions on Internet and Information Systems, vol. 17, no. 9, pp. 2550-2572, 2023. DOI: 10.3837/tiis.2023.09.013.
[ACM Style]
Xueyan Liu, Ruirui Sun, Linpeng Li, Wenjing Li, and Tao Liu. 2023. Black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data. KSII Transactions on Internet and Information Systems, 17, 9, (2023), 2550-2572. DOI: 10.3837/tiis.2023.09.013.
[BibTeX Style]
@article{tiis:56002, title="Black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data", author="Xueyan Liu and Ruirui Sun and Linpeng Li and Wenjing Li and Tao Liu and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2023.09.013}, volume={17}, number={9}, year="2023", month={September}, pages={2550-2572}}