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Linking wireless devices using information contained in Wi-Fi probe requests : Wireless Mobile and Multimedia Networks

Identifieur interne : 000298 ( PascalFrancis/Corpus ); précédent : 000297; suivant : 000299

Linking wireless devices using information contained in Wi-Fi probe requests : Wireless Mobile and Multimedia Networks

Auteurs : Mathieu Cunche ; Mohamed-Ali Kaafar ; Roksana Boreli

Source :

RBID : Pascal:14-0201458

Descripteurs français

English descriptors

Abstract

Active service discovery in Wi-Fi involves wireless stations broadcasting their Wi-Fi fingerprint, i.e. the SSIDs of their preferred wireless networks. The content of those Wi-Fi fingerprints can reveal different types of information about the owner. We focus on the relation between the fingerprints and the links between the owners. Our hypothesis is that social links between devices' owners can be identified by exploiting the information contained in the fingerprint. More specifically we propose to consider the similarity between fingerprints as a metric, with the underlying idea: similar fingerprints are likely to be linked. We first study the performances of several similarity metrics on a controlled dataset and then apply the designed classifier to a dataset collected in the wild. Finally we discuss potential countermeasures and propose a new one based on geolocation. This study is based on a dataset collected in Sydney, Australia, composed of fingerprints belonging to more than 8000 devices.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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A11 02  1    @1 KAAFAR (Mohamed-Ali)
A11 03  1    @1 BORELI (Roksana)
A14 01      @1 INRIA, Rhône-Alpes @2 Grenoble @3 FRA @Z 1 aut. @Z 2 aut.
A14 02      @1 National ICT @3 AUS @Z 2 aut. @Z 3 aut.
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A21       @1 2014
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C01 01    ENG  @0 Active service discovery in Wi-Fi involves wireless stations broadcasting their Wi-Fi fingerprint, i.e. the SSIDs of their preferred wireless networks. The content of those Wi-Fi fingerprints can reveal different types of information about the owner. We focus on the relation between the fingerprints and the links between the owners. Our hypothesis is that social links between devices' owners can be identified by exploiting the information contained in the fingerprint. More specifically we propose to consider the similarity between fingerprints as a metric, with the underlying idea: similar fingerprints are likely to be linked. We first study the performances of several similarity metrics on a controlled dataset and then apply the designed classifier to a dataset collected in the wild. Finally we discuss potential countermeasures and propose a new one based on geolocation. This study is based on a dataset collected in Sydney, Australia, composed of fingerprints belonging to more than 8000 devices.
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C03 12  X  FRE  @0 Australie @2 NG @5 22
C03 12  X  ENG  @0 Australia @2 NG @5 22
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C03 14  X  SPA  @0 Red social @5 24
C03 15  X  FRE  @0 Réseau maillé @5 25
C03 15  X  ENG  @0 Meshed network @5 25
C03 15  X  SPA  @0 Red mallada cerrada @5 25
C03 16  X  FRE  @0 Géolocalisation @4 CD @5 96
C03 16  X  ENG  @0 Geolocation @4 CD @5 96
C03 16  X  SPA  @0 Geolocalización @4 CD @5 96
C07 01  X  FRE  @0 Océanie @2 NG
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C07 01  X  SPA  @0 Oceania @2 NG
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Format Inist (serveur)

NO : PASCAL 14-0201458 INIST
ET : Linking wireless devices using information contained in Wi-Fi probe requests : Wireless Mobile and Multimedia Networks
AU : CUNCHE (Mathieu); KAAFAR (Mohamed-Ali); BORELI (Roksana)
AF : INRIA, Rhône-Alpes/Grenoble/France (1 aut., 2 aut.); National ICT/Australie (2 aut., 3 aut.)
DT : Publication en série; Niveau analytique
SO : Pervasive and mobile computing : (Print); ISSN 1574-1192; Pays-Bas; Da. 2014; Vol. 11; Pp. 56-69; Bibl. 14 ref.
LA : Anglais
EA : Active service discovery in Wi-Fi involves wireless stations broadcasting their Wi-Fi fingerprint, i.e. the SSIDs of their preferred wireless networks. The content of those Wi-Fi fingerprints can reveal different types of information about the owner. We focus on the relation between the fingerprints and the links between the owners. Our hypothesis is that social links between devices' owners can be identified by exploiting the information contained in the fingerprint. More specifically we propose to consider the similarity between fingerprints as a metric, with the underlying idea: similar fingerprints are likely to be linked. We first study the performances of several similarity metrics on a controlled dataset and then apply the designed classifier to a dataset collected in the wild. Finally we discuss potential countermeasures and propose a new one based on geolocation. This study is based on a dataset collected in Sydney, Australia, composed of fingerprints belonging to more than 8000 devices.
CC : 001D04B04G2; 001D02B04; 001D04B03A
FD : Service web; Intergiciel publication souscription; Localisation; Informatique diffuse; Classification; Vie privée; Protocole transmission; Réseau sans fil; Installation intérieure; Métrique; Contremesure; Australie; Confidentialité; Réseau social; Réseau maillé; Géolocalisation
FG : Océanie
ED : Web service; Publish subscribe middleware; Localization; Pervasive computing; Classification; Private life; Transmission protocol; Wireless network; Indoor installation; Metric; Countermeasurement; Australia; Confidentiality; Social network; Meshed network; Geolocation
EG : Oceania
SD : Servicio web; Intergicial editor suscriptor; Localización; Informática difusa; Clasificación; Vida privada; Protocolo transmisión; Red sin hilo; Instalación interior; Métrico; Contramedida; Australia; Confidencialidad; Red social; Red mallada cerrada; Geolocalización
LO : INIST-28186.354000500461690040
ID : 14-0201458

Links to Exploration step

Pascal:14-0201458

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<s5>23</s5>
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<s5>23</s5>
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<s5>24</s5>
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<s5>24</s5>
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<s0>Red social</s0>
<s5>24</s5>
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<s0>Réseau maillé</s0>
<s5>25</s5>
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<s5>25</s5>
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<s5>25</s5>
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<s0>Géolocalisation</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="16" i2="X" l="ENG">
<s0>Geolocation</s0>
<s4>CD</s4>
<s5>96</s5>
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<fC03 i1="16" i2="X" l="SPA">
<s0>Geolocalización</s0>
<s4>CD</s4>
<s5>96</s5>
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<fC07 i1="01" i2="X" l="FRE">
<s0>Océanie</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="X" l="ENG">
<s0>Oceania</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="X" l="SPA">
<s0>Oceania</s0>
<s2>NG</s2>
</fC07>
<fN21>
<s1>251</s1>
</fN21>
<fN44 i1="01">
<s1>OTO</s1>
</fN44>
<fN82>
<s1>OTO</s1>
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<NO>PASCAL 14-0201458 INIST</NO>
<ET>Linking wireless devices using information contained in Wi-Fi probe requests : Wireless Mobile and Multimedia Networks</ET>
<AU>CUNCHE (Mathieu); KAAFAR (Mohamed-Ali); BORELI (Roksana)</AU>
<AF>INRIA, Rhône-Alpes/Grenoble/France (1 aut., 2 aut.); National ICT/Australie (2 aut., 3 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>Pervasive and mobile computing : (Print); ISSN 1574-1192; Pays-Bas; Da. 2014; Vol. 11; Pp. 56-69; Bibl. 14 ref.</SO>
<LA>Anglais</LA>
<EA>Active service discovery in Wi-Fi involves wireless stations broadcasting their Wi-Fi fingerprint, i.e. the SSIDs of their preferred wireless networks. The content of those Wi-Fi fingerprints can reveal different types of information about the owner. We focus on the relation between the fingerprints and the links between the owners. Our hypothesis is that social links between devices' owners can be identified by exploiting the information contained in the fingerprint. More specifically we propose to consider the similarity between fingerprints as a metric, with the underlying idea: similar fingerprints are likely to be linked. We first study the performances of several similarity metrics on a controlled dataset and then apply the designed classifier to a dataset collected in the wild. Finally we discuss potential countermeasures and propose a new one based on geolocation. This study is based on a dataset collected in Sydney, Australia, composed of fingerprints belonging to more than 8000 devices.</EA>
<CC>001D04B04G2; 001D02B04; 001D04B03A</CC>
<FD>Service web; Intergiciel publication souscription; Localisation; Informatique diffuse; Classification; Vie privée; Protocole transmission; Réseau sans fil; Installation intérieure; Métrique; Contremesure; Australie; Confidentialité; Réseau social; Réseau maillé; Géolocalisation</FD>
<FG>Océanie</FG>
<ED>Web service; Publish subscribe middleware; Localization; Pervasive computing; Classification; Private life; Transmission protocol; Wireless network; Indoor installation; Metric; Countermeasurement; Australia; Confidentiality; Social network; Meshed network; Geolocation</ED>
<EG>Oceania</EG>
<SD>Servicio web; Intergicial editor suscriptor; Localización; Informática difusa; Clasificación; Vida privada; Protocolo transmisión; Red sin hilo; Instalación interior; Métrico; Contramedida; Australia; Confidencialidad; Red social; Red mallada cerrada; Geolocalización</SD>
<LO>INIST-28186.354000500461690040</LO>
<ID>14-0201458</ID>
</server>
</inist>
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