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Probe Request Based Device Identification Attack and Defense.

Xiaolin Gu1, Wenjia Wu2, Xiaodan Gu2

  • 1School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China.

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|August 23, 2020
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Summary
This summary is machine-generated.

This study introduces a deep learning method to identify devices using Wi-Fi probe requests, achieving over 99% accuracy. A novel defense mechanism using stream ciphers effectively reduces identification accuracy, enhancing device privacy in Wi-Fi networks.

Keywords:
802.11ac networkdeep learningdevice identificationprobe requeststream cipher

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Wireless Networking

Background:

  • Wi-Fi networks are inherently less secure than wired networks due to their open nature.
  • MAC address randomization is a privacy measure, but attackers can still identify devices using implicit identifiers.
  • Existing methods lack robust defense against sophisticated device identification techniques.

Purpose of the Study:

  • To propose a novel device identification method using 802.11ac probe request frames.
  • To develop an effective defense mechanism against device identification to enhance Wi-Fi privacy.
  • To analyze the efficacy of 802.11ac fields for device identification and privacy protection.

Main Methods:

  • Device identification using deep learning on 802.11ac probe request frames.
  • Analysis of the effectiveness of various 802.11ac fields for identification.
  • Development of a stream cipher-based defense mechanism to encrypt probe request frames.

Main Results:

  • The proposed deep learning method achieved an average f1-score exceeding 99% for device identification.
  • The stream cipher-based defense mechanism reduced the identification method's average f1-score to below 30%.
  • The defense mechanism effectively hides original probe request content while preserving frame construction.

Conclusions:

  • The developed device identification method offers high accuracy in recognizing Wi-Fi devices.
  • The novel defense mechanism significantly mitigates the risk of device identification, bolstering user privacy.
  • The combined attack and defense strategy provides enhanced privacy preservation for devices on Wi-Fi networks.