A differential privacy trajectory data storage and publishing scheme based on radix tree

Abstract

SummaryWith the rapid development of information technology, location‐based services (LBSs) are becoming more and more popular, and at the same time, the users' privacy issues are becoming more and more serious. Therefore, this article proposes a differential private trajectory data storage and publishing scheme based on radix tree (TPRT). Firstly, the original trajectory is preprocessed by considering semantic information and simplified by dividing the stay area to reduce the risk of privacy leakage. Then, differential privacy technology is used to add Laplace noise to sensitive locations to achieve generalization. Finally, a radix tree structure satisfying differential privacy is defined, which alleviates the problem of large space consumption caused by tree height. To protect privacy, Laplace noise is added to the sensitive counts of the radix tree and limited by the Markov chain and privacy degree. Compared with several existing methods, our method has better performance and higher data availability.