Research Article
An Enhanced Approach for Multiple Sensitive Attributes in Data Publishing
@INPROCEEDINGS{10.1007/978-3-030-69514-9_8, author={Haiyan Kang and Yaping Feng and Xiameng Si}, title={An Enhanced Approach for Multiple Sensitive Attributes in Data Publishing}, proceedings={Smart Grid and Internet of Things. 4th EAI International Conference, SGIoT 2020, TaiChung, Taiwan, December 5--6, 2020, Proceedings}, proceedings_a={SGIOT}, year={2021}, month={7}, keywords={Data publishing Multi-sensitive attributes Privacy protection Clustering Dividing}, doi={10.1007/978-3-030-69514-9_8} }- Haiyan Kang
Yaping Feng
Xiameng Si
Year: 2021
An Enhanced Approach for Multiple Sensitive Attributes in Data Publishing
SGIOT
Springer
DOI: 10.1007/978-3-030-69514-9_8
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.
