Private information retrieval in vehicular location-based services

Zheng Tan, Cheng Wang, Mengchu Zhou, Luomeng Zhang

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

8 Scopus citations


Acting as a new type of mobile terminals, vehicles are able to access Internet in real-time. Consequently, a specific kind of Location-Based Services (LBS), usually named Vehicular LBS (VLBS), has received significant attention because of its bright prospects. VLBS can answer drivers' location-dependent queries to Points of Interest and provide more dedicated services for drivers by utilizing transportation information. Accompanying with convenience, however, users may suffer from some serious privacy leak problems. Previous work has proposed a series of privacy protection methods for LBS. As a well-known method for its high effectiveness in protecting privacy, computational Private Information Retrieval (cPIR) can provide provable privacy protection. Yet, it is usually considered impractical because of its prohibitive computational cost. An important research question arises: can cPIR be improved and used in VLBS to preserve privacy? We answer it by proposing a privacy preserving framework for VLBS based on it. Under the restriction of road network, the proposed framework, which applies the available transportation information as prior knowledge for cPIR, can drastically reduce the computational cost. We perform several experiments on a real dataset to validate its effectiveness.

Original languageEnglish (US)
Title of host publicationIEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781467399449
StatePublished - May 4 2018
Event4th IEEE World Forum on Internet of Things, WF-IoT 2018 - Singapore, Singapore
Duration: Feb 5 2018Feb 8 2018

Publication series

NameIEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings


Other4th IEEE World Forum on Internet of Things, WF-IoT 2018

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality


  • Computational Private Information Retrieval (cPIR)
  • Points of Interest (POI)
  • Query Privacy
  • Vehicular Location Based Services (VLBS)


Dive into the research topics of 'Private information retrieval in vehicular location-based services'. Together they form a unique fingerprint.

Cite this