A privacy preserving location service for cloud-of-things system

摘要

The natural characteristics of Location Based Services (LBS) cause potential threats to location privacy. Users need to send their current locations to get the service, which may lead to the leakage of their location privacy. An effective way to protect user's location privacy is to use an imprecise location and send this region to the Cloud-of-things system to replace his real location. When user moves and sends continuous queries, the user needs to transmit the region to the server continuously and an attacker is able to infer the real location from the overlapping regions. In this paper, we propose a novel location privacy pre-protection method for cloud-of things system to preserve user's trajectory privacy. User's moving behaviors are analyzed through Mobility Markov chain. The proposed location cloaking algorithm enlarges the small area to satisfy the user's privacy requirements, so that the location trajectory privacy in the environment of cloud-of-things system is addressed efficiently. Experimental results show the performance of our method in terms of the number of moving steps, the cloaking threshold value, in addition to the user chosen anonymity value. (C) 2018 Elsevier Inc. All rights reserved.