Personalized location anonymity - A kernel density estimation approach

Dapeng Zhao, Jiansong Ma, Xiaoling Wang, Xiuxia Tian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In recent years, the problem of location privacy protection in location-based service (LBS) has drawn a great deal of researchers’ attention. However, the existing technologies of location privacy protection rarely consider the personal visit probability and other side-information, which are likely to be exploited by attackers. In order to protect the users’ location privacy more effectively, we propose a Personal Location Anonymity (PLA) combining side-information to achieve k-anonymity. On the offline phase, we utilize Kernel Density Estimation (KDE) approach to obtain the personal visit probability for each cell of space according to a specific users’ visited locations. On the online phase, the dummy locations for each user’s query can be selected based on both the entropy of personal visit probability and the area of Cloaking Region (CR). We conduct extensive experiments on the real dataset to verify the performance of privacy protection degree, where the privacy properties are measured by the location information entropy and the area of CR.

Original languageEnglish
Title of host publicationWeb-Age Information Management - 17th International Conference, WAIM 2016, Proceedings
EditorsBin Cui, Xiang Lian, Dexi Liu, Nan Zhang, Jianliang Xu
PublisherSpringer Verlag
Pages52-64
Number of pages13
ISBN (Print)9783319399577
DOIs
StatePublished - 2016
Event17th International Conference on Web-Age Information Management, WAIM 2016 - Nanchang, China
Duration: 3 Jun 20165 Jun 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9659
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Web-Age Information Management, WAIM 2016
Country/TerritoryChina
CityNanchang
Period3/06/165/06/16

Keywords

  • Cloaking region
  • K-anonymity
  • Location privacy
  • Location-based services

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