Location based services are commonly used by several mobile applications and services, to provide content related to the area in which the user is located. This enables services such as navigation, particularly useful for vehicular applications, though possibly exposing private information about the user, which has to explicitly grant the location permission. However, smartphone have also many other sensors off the shelf, which currently do not require any permission to be used, and may be leveraged to track the users movements, hence the location, thus raising potentially serious privacy issues. In this paper we present a study which shows that by analyzing data obtained through the accelerometer and the magnetometer, it is possible to achieve less than 50 meters of localization accuracy even for long journeys, and 95% of accuracy on the road identification.

Vehicular Route Identification Using Mobile Devices Integrated Sensors / Bedogni, L.; Bononi, L.. - (2019), pp. 820-825. (Intervento presentato al convegno 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019 tenutosi a jpn nel 2019) [10.1109/PERCOMW.2019.8730753].

Vehicular Route Identification Using Mobile Devices Integrated Sensors

Bedogni L.;
2019

Abstract

Location based services are commonly used by several mobile applications and services, to provide content related to the area in which the user is located. This enables services such as navigation, particularly useful for vehicular applications, though possibly exposing private information about the user, which has to explicitly grant the location permission. However, smartphone have also many other sensors off the shelf, which currently do not require any permission to be used, and may be leveraged to track the users movements, hence the location, thus raising potentially serious privacy issues. In this paper we present a study which shows that by analyzing data obtained through the accelerometer and the magnetometer, it is possible to achieve less than 50 meters of localization accuracy even for long journeys, and 95% of accuracy on the road identification.
2019
2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019
jpn
2019
820
825
Bedogni, L.; Bononi, L.
Vehicular Route Identification Using Mobile Devices Integrated Sensors / Bedogni, L.; Bononi, L.. - (2019), pp. 820-825. (Intervento presentato al convegno 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019 tenutosi a jpn nel 2019) [10.1109/PERCOMW.2019.8730753].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1197995
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