Name
Abstract | ||
|---|---|---|
Outsourcing spatial database to the cloud becomes a paradigm for many applications such as location-bases service (LBS). At the same time, the security of outsourced data and its query becomes a serious issue. In this paper, we consider 3D spherical data that has wide applications in geometric information systems (GIS), and investigate its privacy-preserving query problem. By using an approximately distance-preserving 3D-2D projection method, we first project 3D spatial points to six possible 2D planes. Then we utilize secure Hilbert space-filling curve to encode the 2D points into 1D Hilbert values. After that, we build an encrypted spatial index tree using B(^+)-tree and order-preserving encryption (OPE). Our scheme supports efficient point query, arbitrary polygon query, as well as dynamic updating in the encrypted domain. Theoretical analysis and experimental results on real-word datasets demonstrate its satisfactory tradeoff between security and efficiency. |
Year | Venue | Field |
|---|---|---|
2018 | ICA3PP | Information system,Polygon,Computer science,B-tree,Outsourcing,Theoretical computer science,Encryption,Spatial database,Cloud computing,Distributed computing,Hilbert curve |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
14 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yueyue Zhou | 1 | 0 | 0.34 |
| Tao Xiang | 2 | 4929 | 215.84 |
| Xiaoguo Li | 3 | 19 | 4.67 |