Location Nearest Neighbor Query Scheme in Edge Computing Based on Differential Privacy

Yanni Han, Zhuoqun Li, Jian Zhang, Zhen Wu, Ying Ding

Abstract: In edge computing environments, users are frequently exposed to the hazard of location privacy disclosure when utilizing location-based services (LBS). To address the issue of location privacy breaches in LBS within edge computing, this paper introduces a LBS nearest neighbor query algorithm based on differential privacy. In recognition of the spatial distribution of edge nodes, a novel approach, designated the Geographically Indistinguishable Mechanism in Limited Areas (GIMIA), is proposed to obfuscate the precise location within the coverage of edge nodes. To solve the varying privacy protection budgets required by users across diverse geographical regions, this study further presents a Geographically Indistinguishable Mechanism in Limited Areas based on Spatial Quad-Tree (QGIMIA), according to the regional user density. Experimental findings validate that the data utility and computational time delay of the proposed GIMIA and QGIMIA outperform traditional geographically indistinguishable mechanisms based on Laplace in LBS-based nearest neighbor queries.