Abstract
Location-based service (LBS) brings great benefits to individuals and society, but it also exist serious threat to users’ privacy, because LBS supplier may leak users’ location-related information. It is important to protect users’ privacy while providing LBS. However, current privacy protection and location recommendation service have the problem of timeliness. To address the problem, a location privacy preserving scheme based on Hilbert curve for LBS is proposed. Firstly, a Hilbert curve is generated from given parameters for coordinate transformation to correspond to Hilbert coordinates. Secondly, the points of users are transmitted to the location service provider (LSP) through the randomly generated point of the fog server without using such methods as K anonymous, which satisfy the demand. Then the user’s point of interest (POI) could be obtained by the weighted KNN algorithm of LSP. Finally, the user’s POI would be transmitted back to the client. Simulation results show that the proposed scheme provide location privacy with timeliness.
This work was supported in part by Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics (No. GIIP1805) and Innovation Project of Guangxi Graduate Education (No. YCSW2018140), and Guangxi Science and Technology Plan Project (AD18216004\(\pounds \)AA18118039-2).
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Zhong, Y., Wang, T., Gan, C., Luo, X. (2019). The Location Privacy Preserving Scheme Based on Hilbert Curve for Indoor LBS. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2019. Lecture Notes in Computer Science(), vol 11656. Springer, Cham. https://doi.org/10.1007/978-3-030-26354-6_39
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