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Evaluating Location Privacy in Vehicular Communications and Applications | IEEE Journals & Magazine | IEEE Xplore

Evaluating Location Privacy in Vehicular Communications and Applications


Abstract:

Vehicular ad hoc networks may one day prevent injuries and reduce transportation costs by enabling new safety and traffic management applications, but these networks rais...Show More

Abstract:

Vehicular ad hoc networks may one day prevent injuries and reduce transportation costs by enabling new safety and traffic management applications, but these networks raise privacy concerns because they could enable applications to perform unwanted surveillance. Researchers have proposed privacy protocols, measuring privacy performance based on metrics such as k-anonymity. Because of the frequency and precision of location of queries in vehicular applications, privacy measurement may be improved by considering additional factors. This paper defines continuous network location privacy; presents KDT-anonymity, which is a composite metric including average anonymity set size, i.e., K, average distance deviation, i.e., D, and anonymity duration, i.e., T; derives formulas to calculate theoretical values of K, D, and T; evaluates five privacy protocols under realistic vehicle mobility patterns using KDT-anonymity; and compares KDT-anonymity with prior metrics.
Published in: IEEE Transactions on Intelligent Transportation Systems ( Volume: 17, Issue: 9, September 2016)
Page(s): 2658 - 2667
Date of Publication: 29 February 2016

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I. Introduction

Vehicular ad-hoc networks (VANETs) present uniquely complex location privacy challenges because they utilize protocols which are not used in other networks. For example, in the United States VANET standards are specified by Dedicated Short Range Communications/Wireless Access in Vehicular Environments (DSRC/WAVE), which uses WAVE short message protocol (WSMP). DSRC is designed to send frequent MAC-layer safety messages. DSRC can be used to access location based services (LBS) which also may require frequent precise location (FPL) data.

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