Breaching the privacy of connected vehicles network

TL;DR

This paper demonstrates that connected vehicle networks, despite their privacy measures, can be vulnerable to privacy breaches by reconstructing driver paths from accessible driving attributes.

Contribution

It introduces a novel method for reconstructing driver routes using only driving attributes, highlighting potential privacy risks in connected vehicle systems.

Findings

Driver paths can be reconstructed without knowing trip destinations.

Analyzing cornering, speed, and time reveals sensitive route information.

Privacy vulnerabilities exist even with minimal shared data.

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 (UBI), 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 the path of driver 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 path of driver, while not knowing the target point of the trip.