Abstract
Today’s applications and providers are very interested in knowing the social aspects of users in order to customize the services they provide and to be more effective. Among the others, the most frequented places and the paths to reach them are information that turns out to be very useful to define users’ habits. The most exploited means to acquire positions and paths is the GPS sensor, however it has been shown how leveraging inertial data from installed sensors can lead to path identification. In this work, we present a Computationally Efficient algorithm to Reconstruct Vehicular Traces (CERT), a novel algorithm which computes the path traveled by a vehicle using accelerometer and magnetometer data. We show that by analyzing data obtained through the accelerometer and the magnetometer in vehicular scenarios, CERT achieves almost perfect identification for medium and small sized cities. Moreover, we show that the longer the path, the easier it is to recognize it. We also present results characterizing the privacy risks depending on the area of the world, since, as we show, urban dynamics play a key role in the path detection.
Highlights
In our everyday life, we leverage a lot of services that support us in several activities
To extend our study to multiple cities and on longer road paths, we develop a custom simulator, which provides inertial sensors data for vehicles driving in a given road map
We are interested in understanding how such a system can be effectively used in practice, and if the city dynamics plays a role in the possibility to recognize paths performed by users
Summary
We leverage a lot of services that support us in several activities. Such services are more effective if they take into consideration the information of the user that exploits them in order to provide a more customized support. To this end, applications and providers are interested in getting information about the social aspects of users. Applications and providers are interested in getting information about the social aspects of users Two of these social aspects are the most frequented places and the paths of a user. One way is to exploit Inertial Measurement Units (IMUs), which are nowadays present in a multitude of devices, including smartphones, tablets and cars
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