Abstract
With the development of the e-commerce and the logistics industry, more and more personal information has been collected by the third-party logistics. The personalized privacy protection problem with multiple sensitive attributes is seldom considered in data publishing. To solve this problem, a method of Multi-sensitive attributes Weights Clustering and Dividing (MWCD) is proposed. Firstly, set the corresponding weight for each sensitive attribute value considering the different requirements of users and then cluster the data based on the weights. Secondly, divide the records by level rule to select record for l-diversity. Finally, publish data based on the idea of Multi-Sensitive Bucketization. The experimental results indicate that the release ratio of the important data though the proposed algorithm is above 95%, and the execution time is shorter.
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Acknowledgment
This work is partially supported by Humanities and social sciences research project of the Ministry of Education (No. 20YJAZH046), fund of Bistu promoting the connotation development of universities and improving the scientific research level (No. 2019KYNH219), and Natural Science Foundation of China (No. 61370139).
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Kang, H., Feng, Y., Si, X. (2021). An Enhanced Approach for Multiple Sensitive Attributes in Data Publishing. In: Lin, YB., Deng, DJ. (eds) Smart Grid and Internet of Things. SGIoT 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 354. Springer, Cham. https://doi.org/10.1007/978-3-030-69514-9_8
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DOI: https://doi.org/10.1007/978-3-030-69514-9_8
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