Identifying device type from cross channel probe request behavior
Wyatt Praharenka, Ioanis Nikolaidis · 2021
Across different Wi-Fi devices, there exist differences in the probing behavior during active scanning. We conjecture that the behavior is sufficiently distinct to identify individual device types. We propose a feature engineering strategy to training machine learning algorithms for determination of the device type. We propose a concurrent capture across multiple Wi-Fi channels, thus allowing the features to include attributes for the transitions happening between channels during active scanning. Small-scale proof-of-concept results provide encouraging results about the method's potential.