边缘计算下面向位置隐私保护的中继分流模型

doi:10.3969/j.issn.0255-8297.2020.05.006

Abstract

Abstract: With the widespread adoption of location-based services, people pay more and more attention to the issue of location privacy protection. The dummy based location privacy protection method could achieve the goal via mixing fake locations with users; real location. However, most of traditional dummy based location privacy protection methods are deployed in remote cloud servers, which brings performance limitation issue such as long delay for users to obtain computation results. To address this problem, we consider migrating the dummy based location privacy protection method from cloud servers to edge servers. Moreover, in view of the upper limit of service capacity and coverage of edge servers, we propose a relay offloading model for location privacy protection. We implement the offloading method and run our method with a real data set. Experimental results verify that our method can reduce the delay for user to obtain computation results while ensuring the effect of user;s location privacy protection.

Key words: edge computing, location privacy protection, computation offloading, k-anonymity

CLC Number:

TP3-0

LIN Wenmin, ZHANG Song, LIU Jiabang. Relay-Assisted Offloading Model for Location Privacy Protection under Edge Computing[J]. Journal of Applied Sciences, 2020, 38(5): 724-741.

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Relay-Assisted Offloading Model for Location Privacy Protection under Edge Computing

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