| Title | A Dummy-Based Privacy Protection Scheme for Location-Based Services under Spatiotemporal Correlation |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Diao, Yiqing, Ye, Ayong, Cheng, Baorong, Zhang, Jiaomei, Zhang, Qiang |
| Conference Name | 2020 International Conference on Networking and Network Applications (NaNA) |
| Date Published | Dec. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-8954-3 |
| Keywords | Collaboration, composability, Correlation, cryptology, dummies, historical query trajectory, Human Behavior, human factors, location association, Logic gates, Metrics, privacy, Proposals, pubcrawl, resilience, resilient, Scalability, security, Spatiotemporal phenomena, Trajectory, trajectory privacy |
| Abstract | The dummy-based method has been commonly used to protect the users location privacy in location-based services, since it can provide precise results and generally do not rely on a third party or key sharing. However, the close spatiotemporal correlation between the consecutively reported locations enables the adversary to identify some dummies, which lead to the existing dummy-based schemes fail to protect the users location privacy completely. To address this limit, this paper proposes a new algorithm to produce dummy location by generating dummy trajectory, which naturally takes into account of the spatiotemporal correlation all round. Firstly, the historical trajectories similar to the user's travel route are chosen as the dummy trajectories which depend on the distance between two trajectories with the help of home gateway. Then, the dummy is generated from the dummy trajectory by taking into account of time reachability, historical query similarity and the computation of in-degree/out-degree. Security analysis shows that the proposed scheme successfully perturbs the spatiotemporal correlation between neighboring location sets, therefore, it is infeasible for the adversary to distinguish the users real location from the dummies. Furthermore, extensive experiments indicate that the proposal is able to protect the users location privacy effectively and efficiently. |
| URL | https://ieeexplore.ieee.org/document/9353752 |
| DOI | 10.1109/NaNA51271.2020.00081 |
| Citation Key | diao_dummy-based_2020 |
A Dummy-Based Privacy Protection Scheme for Location-Based Services under Spatiotemporal Correlation