Maximum Influential Location Selection With Differentially Private User Locations

Sehwa Park, Junkyu Lee, Seog Park · IEEE Access · 2020

The widespread use of mobile devices and social network services has made optimal location queries an important research topic. Previous studies have focused on the problem of maximum influential (Max-inf) location selection, that is, finding a location that can attract as many clients as possible. The location information of each client should be collected to process such a query. However, client location is considered sensitive information. Therefore, a privacy protection technique should be applied to Max-inf problems. Motivated by this, we propose a Max-inf problem query-processing technique with differentially private client location information. Furthermore, we present a Voronoi region-based technique to guarantee query accuracy and a Voronoi envelope-based pruning heuristic to improve query performance.

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