Computer Science ›› 2017, Vol. 44 ›› Issue (9): 156-161.doi: 10.11896/j.issn.1002-137X.2017.09.030

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Hierarchical Privacy Protection of Multi-source Data Fusion for Sensitive Value

YANG Yue-ping, WANG Jian and XUE Ming-fu   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Data fusion technology enables users to get more comprehensive data to provide more effective service.Howe-ver,the existing multi-source data fusion privacy protection models do not consider the importance of the data provi-ders,and the sensitivity of different attributes and attribute values.According to the above problems,this paper proposed a hierarchical privacy model for sensitive value.The model enables data providers to set sensitive value of data attributes and attribute values by anonymous degree requirements to realize the individual privacy protection of sensitive values.At the same time,this paper proposed a multi-source data fusion privacy protection algorithm for sensitive value combining with k-anonymous privacy model and the top-to-down specialization TDS.Experiments show that the proposed algorithm can not only realize data security fusion,but also obtain better privacy protection.

Key words: Data integration,Sensitivity,Hierarchical privacy mode,k-anonymous

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