Privacy preserving dynamic data release against synonymous linkage based on microaggregation

The rapid development of the mobile Internet coupled with the widespread use of intelligent terminals have intensified the digitization of personal information and accelerated the evolution of the era of big data. The sharing and publishing of various big data brings convenience and also increases the risk of personal privacy leakage. In order to reduce users' privacy leakage that may be caused by data release, many privacy preserving data publishing methods have been proposed by scientists in both academia and industry in the recent years. However, non-numerical sensitive information has natural semantic relevance, and therefore, synonymous linkages may still exist and cause serious privacy disclosures in privacy protection methods based on an anonymous model. To address this issue, this paper proposes a privacy preserving dynamic data publishing method based on microaggregation. A series of indicators are accordingly designed to evaluate the synonymous linkages between the non-numerical sensitive values which in turn facilitate in improving the clustering effect of the microaggregation anonymous method. The dynamic update program is introduced into the proposed microaggregation method to realize the dynamic release and update of data. Experimental analysis suggests that the proposed method provides better privacy protection effect and availability of published data in contrast to the state-of-the-art methods.

Automated summary

The rapid development of the mobile Internet and widespread use of intelligent terminals have accelerated the digitization of personal information and the evolution of the big data era. Sharing and publishing big data bring convenience but also increase the risk of personal privacy leakage. To reduce privacy leakage caused by data release, various privacy preserving data publishing methods have been proposed. However, non-numerical sensitive information may still have semantic relevance, leading to serious privacy disclosures. This paper introduces a privacy preserving dynamic data publishing method based on microaggregation to address this issue, which shows better privacy protection and availability of published data compared to existing methods.