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Identification of mobile phones using the built-in magnetometers stimulated by motion patterns
ID
Baldini, Gianmarco
(
Avtor
),
ID
Dimc, Franc
(
Avtor
),
ID
Kamnik, Roman
(
Avtor
),
ID
Steri, Gary
(
Avtor
),
ID
Giuliani, Raimondo
(
Avtor
),
ID
Gentile, Claudio
(
Avtor
)
PDF - Predstavitvena datoteka,
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(1,45 MB)
MD5: C0271F72D2013F975AC0EAA800F0C7F3
URL - Izvorni URL, za dostop obiščite
http://www.mdpi.com/1424-8220/17/4/783
Galerija slik
Izvleček
We investigate the identification of mobile phones through their built-in magnetometers. These electronic components have started to be widely deployed in mass market phones in recent years, and they can be exploited to uniquely identify mobile phones due their physical differences, which appear in the digital output generated by them. This is similar to approaches reported in the literature for other components of the mobile phone, including the digital camera, the microphones or their Radio Frequency (RF) transmission components. In this paper, the identification is performed through an inexpensive device made up of a platform that rotates the mobile phone under test and a fixed magnet positioned on the edge of the rotating platform. When the mobile phone passes in front of the fixed magnet, the built-in magnetometer is stimulated, and its digital output is recorded and analyzed. For each mobile phone, the experiment is repeated over six different days to ensure consistency in the results. A total of 10 phones of different brands and models or of the same model were used in our experiment. The digital output from the magnetometers is synchronized and correlated, and statistical features are extracted to generate a fingerprint of the built-in magnetometer and, consequently, of the mobile phone. A Support Vector Machine (SVM) machine learning algorithm is used to classify the mobile phones on the basis of the extracted statistical features. Our results show that inter-model classification (i.e., different models and brands classification) is possible with great accuracy, but intra-model (i.e., phones with different serial numbers and same model) classification is more challenging, the resulting accuracy being just slightly above random choice.
Jezik:
Angleški jezik
Ključne besede:
mobile phones
,
fingerprinting
,
magnetometers
Vrsta gradiva:
Članek v reviji
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FPP - Fakulteta za pomorstvo in promet
FE - Fakulteta za elektrotehniko
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2017
Št. strani:
19 str.
Številčenje:
Vol. 17, iss. 4, art. 783
PID:
20.500.12556/RUL-131164
UDK:
621.395
ISSN pri članku:
1424-8220
DOI:
10.3390/s17040783
COBISS.SI-ID:
2808419
Datum objave v RUL:
23.09.2021
Število ogledov:
1242
Število prenosov:
198
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
Sensors
Skrajšan naslov:
Sensors
Založnik:
MDPI
ISSN:
1424-8220
COBISS.SI-ID:
10176278
Licence
Licenca:
CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:
http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:
To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:
06.04.2017
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
mobilni telefoni
,
prstni odtisi
,
magnetometri
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