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Fingerprinting connected Wi-Fi devices using per-network MAC addresses

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  • معلومة اضافية
    • Contributors:
      Privacy Models, Architectures and Tools for the Information Society (PRIVATICS); Inria Grenoble - Rhône-Alpes; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-CITI Centre of Innovation in Telecommunications and Integration of services (CITI); Institut National des Sciences Appliquées de Lyon (INSA Lyon); Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon); Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Inria Lyon; Institut National de Recherche en Informatique et en Automatique (Inria); CITI Centre of Innovation in Telecommunications and Integration of services (CITI); Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)
    • بيانات النشر:
      HAL CCSD
    • الموضوع:
      2024
    • Collection:
      Université de Lyon: HAL
    • الموضوع:
    • الموضوع:
      Montréal, Canada
    • نبذة مختصرة :
      International audience ; Wi-Fi stands out as one of the most prominent and widespread wireless technologies in use today. Smartphones and various other Wi-Fi-enabled devices employ management frames called probe-requests to discover nearby networks.In this study, we reveal that it is possible to fingerprint based on the probe-requests they emit while connected to a network. Leveraging distinctive features of probe-request bursts we use a Random Forest-based approach to successfully fingerprint devices. This demonstrate that device randomizing their MAC addresses between networks can still be tracked. Through an assessment conducted on a real-world measurement comprising Wi-Fi devices with diverse operating systems, and spanning a month duration, we demonstrate that our model fingerprints individual devices with around 40% accuracy with 1 burst and perfect re-identification if two or more bursts are available.
    • الدخول الالكتروني :
      https://hal.science/hal-04655338
      https://hal.science/hal-04655338v1/document
      https://hal.science/hal-04655338v1/file/Fingerprinting_connected_Wi_Fi_devices_using_per_network_MAC_addresses___SECAI.pdf
    • Rights:
      http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.E244A2BD