EV-Linker: Mapping eavesdropped Wi-Fi packets to individuals via electronic and visual signal matching

• We propose a new attack EV-Linker to map eavesdropped Wi-Fi packets to individuals.
• We solve the challenges caused by the devices, environment and people's movements.
• EV-Linker considers both moving and stationary people.
• Experiments demonstrate the effectiveness of EV-Linker.

Due to the broadcast nature of Wi-Fi, attackers can easily steal users' privacy by eavesdropping. Such attacks are in full force when packets captured can be quickly mapped to individuals. Nevertheless, this task is non-trivial in most public environments with more than one stranger because packets only include device identities (MAC addresses). We observe that cameras can help attackers to identify users, and moreover, both visual signal (i.e., the body size in the images) and electronic signal (i.e., RSSI) are affected by the relative motion between the user and the surveillance equipment. Leveraging this observation, we propose a new attack EV-Linker to achieve this goal by matching the distance information hidden in electronic and visual signals. We consider both scenarios with moving and motionless persons. Our evaluation results demonstrate that EV-Linker can effectively couple the devices with the owners, whether they are moving or not, with high accuracy.