Location Privacy-Preserving Method Based on Historical Proximity Location release_leejj6pudvh3lkpmdazjrkvcaa

by Xueying Guo, Wenming Wang, Haiping Huang, Qi Li, Reza Malekian

Published in Wireless Communications and Mobile Computing by Hindawi Limited.

2020   Volume 2020, p1-16

Abstract

With the rapid development of Internet services, mobile communications, and IoT applications, Location-Based Service (LBS) has become an indispensable part in our daily life in recent years. However, when users benefit from LBSs, the collection and analysis of users' location data and trajectory information may jeopardize their privacy. To address this problem, a new privacy-preserving method based on historical proximity locations is proposed. The main idea of this approach is to substitute one existing historical adjacent location around the user for his/her current location and then submit the selected location to the LBS server. This method ensures that the user can obtain location-based services without submitting the real location information to the untrusted LBS server, which can improve the privacy-preserving level while reducing the calculation and communication overhead on the server side. Furthermore, our scheme can not only provide privacy preservation in snapshot queries but also protect trajectory privacy in continuous LBSs. Compared with other location privacy-preserving methods such as <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>k</mml:mi></mml:math>-anonymity and dummy location, our scheme improves the quality of LBS and query efficiency while keeping a satisfactory privacy level.
In application/xml+jats format

Archived Files and Locations

application/pdf  2.0 MB
file_lmipclhptjdanbz22ezau4eqjq
downloads.hindawi.com (publisher)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   published
Date   2020-07-18
Language   en ?
Container Metadata
Open Access Publication
In DOAJ
In Keepers Registry
ISSN-L:  1530-8669
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 216d21b5-619c-4de0-ac5c-a299fbbcc7b7
API URL: JSON