Abstract
Nowadays, spatial search services bring unprecedented convenience in people’s daily life (e.g., location-based services, social networking) and are becoming more and more popular. To protect the privacy of outsourcing data, several schemes have been proposed to achieve secure search over encrypted spatial databases. However, most existing schemes cannot support dynamic updates, which seriously hinders the practical application of spatial databases. To address this issue, in this paper, we propose two novel Spatial Dynamic Searchable Encryption (SDSE) constructions for outsourcing spatial databases, which achieve various security guarantees. First, we present a basic construction supporting dynamic update with sub-linear search complexity based on the order-revealing encryption and Quadtree. Then, to ensure that updates do not reveal any information underlying the prior modifications beyond some explicit leakage (i.e., forward security), we further give an improved construction according to constrained pseudo-random functions. Both the nearest neighbor search and geometric search are supported in our constructions, which meet almost all spatial search needs. The experiments using real-world dataset demonstrate that our constructions are efficient and feasible in practice.
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Notes
- 1.
Here, Search denotes both NNSearch and GeoSearch.
- 2.
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Acknowledgments
This work was supported by the Key Program of NSFC Grant (U1405255), Shaanxi Science & Technology Coordination & Innovation Project (2016TZC-G-6-3), the Fundamental Research Funds for the Central Universities (SA-ZD161504, JB191506), the National Natural Science Foundation of China (61702404, U1804263, 61702105), and the National Natural Science Foundation of Shaanxi Province (2019JQ-005). Xiangyu Wang was supported by the Doctoral Students’ Short Term Study Abroad Scholarship, Xidian University.
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Wang, X., Ma, J., Liu, X., Miao, Y., Zhu, D. (2020). Spatial Dynamic Searchable Encryption with Forward Security. In: Nah, Y., Cui, B., Lee, SW., Yu, J.X., Moon, YS., Whang, S.E. (eds) Database Systems for Advanced Applications. DASFAA 2020. Lecture Notes in Computer Science(), vol 12113. Springer, Cham. https://doi.org/10.1007/978-3-030-59416-9_48
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