A Trajectory-Privacy Protection Method Based on Location Similarity of Query Destinations in Continuous LBS Queries

Lu Zhang, Saide Zhu, Fengyin Li, Ruinian Li, Jing Meng, Wei Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In the continuous location-based service (LBS) queries, the trajectory k-anonymity method that incorporates user’s moving trend is becoming popular because of its high quality of service (QoS). The existing works often apply user’s moving direction to represent the user’s moving trend. However, the query destinations of the users with closer moving directions are not necessarily closer. As a result, the users in a cloaked set may diverge with the proceeding of the continuous queries, leading to large cloaked areas as well as a reduction of QoS. Therefore, in this paper, a new concept named “location similarity of query destination (LS-QD)”, is proposed to reflect user’s global moving trend. By incorporating LS-QD, we develop a novel trajectory k-anonymity method for continuous LBS queries. Our system architecture utilizes a quadtree model with a pyramid structure to construct the user cloaked sets conveniently. Both theoretical analysis and simulation experiments are carried out to evaluate the robustness and security performance of our proposed method. Compared with other existing methods, our LS-QD based k-anonymity method can reduce the cloaking area and cloaking time while increasing the cloaking success ratio by about 40%–70%, which demonstrates its superiority in guaranteeing QoS for continuous LBS queries.

Original languageEnglish (US)
Title of host publicationWireless Algorithms, Systems, and Applications - 15th International Conference, WASA 2020, Proceedings
EditorsDongxiao Yu, Falko Dressler, Jiguo Yu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages704-715
Number of pages12
ISBN (Print)9783030590154
DOIs
StatePublished - 2020
Event15th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2020 - Qingdao, China
Duration: Sep 13 2020Sep 15 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12384 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2020
Country/TerritoryChina
CityQingdao
Period9/13/209/15/20

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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