Breaching the privacy of connected vehicles network

Vladimir Kaplun and Michael Segal ()
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Vladimir Kaplun: Ben-Gurion University of the Negev
Michael Segal: Ben-Gurion University of the Negev

Telecommunication Systems: Modelling, Analysis, Design and Management, 2019, vol. 70, issue 4, No 4, 555 pages

Abstract: Abstract Connected vehicles network is designed to provide a secure and private method for drivers to use the most efficiently the roads in certain area. When dealing with the scenario of car to access points connectivity (Wi-Fi, 3G, LTE), the vehicles are connected by central authority like cloud. Thus, they can be monitored and analyzed by the cloud which can provide certain services to the driver, i.e. usage based insurance, entertainment services, navigation etc. The main objective of this work is to show that by analyzing the information about a driver which is provided to the usage based insurance companies, it is possible to get additional private data, even if the basic data in first look, seems not so harmful. In this work, we present an analysis of a novel approach for reconstructing driver’s path from other driving attributes, such as cornering events, average speed and total driving time. We show that, in some cases, it is possible to reconstruct the driver’s path, while not knowing the target point of the trip.

Keywords: Privacy; Connected vehicles networks; Data breach; Usage-based insurance (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11235-018-00544-6

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