A Semantic-Based Approach for Privacy-Preserving in Trajectory Publishing

Abstract

The increasing abundance of data in the trajectories of personal movement opens up new opportunities for analyzing and mining human mobility. But the inherent personal information in the data raises the privacy concern. In this paper, the trajectories are not simply considered as a sequence of the coordinates in Euclidean space, they combine the semantics-aware information with the background knowledge of underlying map for the location points. A novel approach is then proposed to conceal the actually visited sensitive places. To this end, a cloaking region for each personalized sensitive place is built before a reasonable dummy trajectory in the cloaking region is constructed. The performance of our approach is evaluated based on a real-world trajectories dataset. And the results show that the proposed approach outperforms the existing privacy-preserving approaches. INDEX TERMS Trajectory publishing, privacy-preserving, semantic.

Trajectory Privacy Protection Based on Sensitive Stay Area Replacement in Publishing

“…find new position with Dis(D, L e+k ′ ) � dis k (13) end for (14) trajectory. e measurement of similarity can not only be conducted in time and space, but also in the trajectory shape.…”

“…STDP in reference [13] selected a POI in sensitive areas containing k − 1 POI points which are similar to the sensitive points. SBA in reference [14] selected the same type of POI based on the classification tree of POI in the cloaking region. e availability of each scheme is measured by trajectory location distance, trajectory shape distance, and trajectory distance.…”

“…Tan et al [13] proposed semantic trajectory anonymizing based on the k-anonymity model, in which, there are sensitive areas that contain k − 1 POI(Points of Interest) points that are similar to the sensitive points, and trajectory ambiguity is executed based on the motion modes, road network topologies and road weights in the sensitive area. Ye et al [14] proposed a novel approach to conceal the actually visited sensitive place. e trajectories are not simply considered as a sequence of the coordinates in Euclidean space, but they combine the semantics-aware information with the background knowledge of the underlying map for the location points.…”

A Blockchain-Based Location Privacy-Preserving Scheme in Location-Based Service

“…As the threat of semantic attacks to privacy becomes more and more serious, the methods to enhance the protection of personal semantic privacy also attract the attention of academic circles. To enhance semantic privacy level with physical constrain, Ye et al in [26] considered roadnetwork semantic information to choose anonymous location for anonymization. Combining the semantics-aware information with the background semantic knowledge of the underlying map, a novel approach is proposed to anonymization and thus conceal the visited places.…”

“…Second, semantic information brings a new challenge to the anonymity set. While exploiting the feature that semantic information can reflect the deeper implicit content of transactions can improve the accuracy of the model, it also creates new challenges for privacy protection [26,27]. Semantic information can help an attacker to identify the true location in an anonymous set although anonymity has been achieved.…”