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

Identifieur interne : 005B64 ( PascalFrancis/Curation ); précédent : 005B63; suivant : 005B65

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

Auteurs : Mathieu Cunche [France] ; Mohamed-Ali Kaafar [France, Australie] ; Roksana Boreli [Australie]

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.
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A11 02  1    @1 KAAFAR (Mohamed-Ali)
A11 03  1    @1 BORELI (Roksana)
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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 02  X  SPA  @0 Intergicial editor suscriptor @5 07
C03 03  X  FRE  @0 Localisation @5 08
C03 03  X  ENG  @0 Localization @5 08
C03 03  X  SPA  @0 Localización @5 08
C03 04  X  FRE  @0 Informatique diffuse @5 09
C03 04  X  ENG  @0 Pervasive computing @5 09
C03 04  X  SPA  @0 Informática difusa @5 09
C03 05  X  FRE  @0 Classification @5 10
C03 05  X  ENG  @0 Classification @5 10
C03 05  X  SPA  @0 Clasificación @5 10
C03 06  X  FRE  @0 Vie privée @5 11
C03 06  X  ENG  @0 Private life @5 11
C03 06  X  SPA  @0 Vida privada @5 11
C03 07  X  FRE  @0 Protocole transmission @5 12
C03 07  X  ENG  @0 Transmission protocol @5 12
C03 07  X  SPA  @0 Protocolo transmisión @5 12
C03 08  X  FRE  @0 Réseau sans fil @5 18
C03 08  X  ENG  @0 Wireless network @5 18
C03 08  X  SPA  @0 Red sin hilo @5 18
C03 09  X  FRE  @0 Installation intérieure @5 19
C03 09  X  ENG  @0 Indoor installation @5 19
C03 09  X  SPA  @0 Instalación interior @5 19
C03 10  X  FRE  @0 Métrique @5 20
C03 10  X  ENG  @0 Metric @5 20
C03 10  X  SPA  @0 Métrico @5 20
C03 11  X  FRE  @0 Contremesure @5 21
C03 11  X  ENG  @0 Countermeasurement @5 21
C03 11  X  SPA  @0 Contramedida @5 21
C03 12  X  FRE  @0 Australie @2 NG @5 22
C03 12  X  ENG  @0 Australia @2 NG @5 22
C03 12  X  SPA  @0 Australia @2 NG @5 22
C03 13  X  FRE  @0 Confidentialité @5 23
C03 13  X  ENG  @0 Confidentiality @5 23
C03 13  X  SPA  @0 Confidencialidad @5 23
C03 14  X  FRE  @0 Réseau social @5 24
C03 14  X  ENG  @0 Social network @5 24
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
C07 01  X  ENG  @0 Oceania @2 NG
C07 01  X  SPA  @0 Oceania @2 NG
N21       @1 251
N44 01      @1 OTO
N82       @1 OTO

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Pascal:14-0201458

Le document en format XML

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<s5>25</s5>
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<fC03 i1="16" i2="X" l="FRE">
<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>
</fC03>
<fC03 i1="16" i2="X" l="SPA">
<s0>Geolocalización</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<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>
</fN82>
</pA>
</standard>
</inist>
</record>

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