| Title | Trajectory Anonymity Based on Quadratic Anonymity |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Junjie, Jia, Haitao, Qin, Wanghu, Chen, Huifang, Ma |
| Conference Name | 2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE) |
| Keywords | adjacent anonymous area, anonymity, composability, Computer science, current sensitive region, data privacy, data protection, Euclidean distance, forged location, Human Behavior, k-anonymity, K-anonymous, Location area division, location mapping, Location mappings, Metrics, original location, original Regional anonymity, Perturbation methods, privacy, privacy information, pubcrawl, quadratic anonymity, resilience, Resiliency, Sensitive region, Servers, Synchronous trajectory, synchronous trajectory data, Trajectory, trajectory anonymity publishing, trajectory anonymous algorithm |
| Abstract | Due to the leakage of privacy information in the sensitive region of trajectory anonymity publishing, which is resulted by the attack, this paper aims at the trajectory anonymity algorithm of division of region. According to the start stop time of the trajectory, the current sensitive region is found with the k-anonymity set on the synchronous trajectory. If the distance between the divided sub-region and the adjacent anonymous area is not greater than the threshold d, the area will be combined. Otherwise, with the guidance of location mapping, the forged location is added to the sub-region according to the original location so that the divided sub-region can meet the principle of k-anonymity. While the forged location retains the relative position of each point in the sensitive region, making that the divided sub-region and the original Regional anonymity are consistent. Experiments show that compared with the existing trajectory anonymous algorithm and the synchronous trajectory data set with the same privacy, the algorithm is highly effective in both privacy protection and validity of data quality. |
| DOI | 10.1109/EITCE47263.2019.9094777 |
| Citation Key | junjie_trajectory_2019 |
Trajectory Anonymity Based on Quadratic Anonymity