Using the channel state of a Wi-Fi transmission an attacker can extract keystrokes a victim presses on a 10-digit number pad. Other research groups have already shown such an attack to be possible to perform on keyboards and number pads, but have not explored the limitations of this attack. This work builds such a keylogger to show that it is possible to detect and identify keystrokes using only signals from a nearby Wi-Fi network as a side channel and find the limits of such an attack. For this, we run multiple experiments with different parameters changed, like distance or missing line of sight, and evaluate the results of the keylogger. We found that with our current setup, we are able to achieve good results in key detection with over 90 % in both precision and recall, but are unable to identify keys. Additionally, we found that introducing unrelated movement deteriorates the results, while increasing the distance between the devices or removing line of sight barely impacts the result of the keylogger.
Jan 2023
Completed (September 2023)