About this article
Published Online: Jul 03, 2015
Page range: 111 - 118
DOI: https://doi.org/10.1515/cait-2015-0032
Keywords
© by Chen Wen
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Check-in service, being one of the most popular services in Mobile Social Network Services (MSNS), has serious personal privacy leakage threats. In this paper check-in sequences of pseudonym users were buffered, and a bit matrix for buffered check-in sequences was built, which can achieve privacy guarantee of k-anonymity. The method guarantees that the number of lost check-in locations is minimized while satisfying users’ privacy requirements. Besides, it also reduces the cost of finding a trajectory k-anonymity set. At last, the results of a set of comparative experiments with (k, δ)-anonymity on real world datasets show the method accuracy and efficiency.