Location Privacy Challenges in Mobile Edge Computing: Classification and Exploration

Abstract

LPPMs have been well surveyed based on the view of methodologies, attacks, and so on. It has long been ignored that LBS applicability will be sacrificed due to the implementation of LPPMs. Existing and future LPPMs should clearly claim LBS applicability. This is essential for future research on location privacy in the MEC environment because of the diversity development of the LBS. To realize this goal, in this article, we present a classification of LBS by dividing the LBS into three independent dimensions, and we list a brief sample of LBS applicability of typical LPPMs based on our LBS categories. Then we consider even further new trends of LBS in MEC and introduce a new type of LBS named DLBS. We explain that DLBS subverts the existing LPPM problem, and we present a conceptual method to cope with the location privacy threat from DLBS.