Breaching the privacy of connected vehicles network View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-04

AUTHORS

Vladimir Kaplun, Michael Segal

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. More... »

PAGES

541-555

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11235-018-00544-6

DOI

http://dx.doi.org/10.1007/s11235-018-00544-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111513471


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