Differentially private location protection with continuous time stamps for VANETs

  • Zhili Chen
  • , Xianyue Bao
  • , Zuobin Ying*
  • , Ximeng Liu
  • , Hong Zhong
  • *Corresponding author for this work

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

7 Scopus citations

Abstract

Vehicular Ad hoc Networks (VANETs) have higher requirements of continuous Location-Based Services (LBSs). However, the untrusted server could reveal the users’ location privacy in the meantime. Syntactic-based privacy models have been widely used in most of the existing location privacy protection schemes. Whereas, they are suffering from background knowledge attacks, neither do they take the continuous time stamps into account. Therefore we propose a new differential privacy definition in the context of location protection for the VANETs, and we designed an obfuscation mechanism so that fine-grained locations and trajectories will not exposed when vehicles request location-based services on continuous time stamps. Then, we apply the exponential mechanism in the pseudonym permutations to provide disparate pseudonyms for different vehicles when making requests on different time stamps, these pseudonyms can hide the position correlation of vehicles on consecutive time stamps besides releasing them in a coarse-grained form simultaneously. The experimental results on real-world datasets indicate that our scheme significantly outperforms the baseline approaches in data utility.

Original languageEnglish
Title of host publicationAlgorithms and Architectures for Parallel Processing - 18th International Conference, ICA3PP 2018, Proceedings
EditorsJaideep Vaidya, Jin Li
PublisherSpringer Verlag
Pages204-219
Number of pages16
ISBN (Print)9783030050627
DOIs
StatePublished - 2018
Externally publishedYes
Event18th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2018 - Guangzhou, China
Duration: 15 Nov 201817 Nov 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11337 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2018
Country/TerritoryChina
CityGuangzhou
Period15/11/1817/11/18

Keywords

  • Continuous time stamps
  • Differential privacy
  • LBS
  • Location privacy
  • VANETs

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