Academy & Industry Research Collaboration Center (AIRCC)

Volume 11, Number 18, November 2021

Smartphone Model Fingerprinting using WiFi Radiation Patterns


Thomas Burton and Kasper Rasmussen, University of Oxford, UK


This paper aims to demonstrate the feasibility of our proposed method for fingerprinting different classes of wireless devices. Our method relies on the observation that different device types, or indeed different models of the same type, have different wireless radiation patterns. We show in detail how a small set of stationary receivers can measure the radiation pattern of a transmitting device in a completely passive manner. As the observed device moves, our method can gather enough data to characterize the shape of the radiation pattern, which can be used to determine the type of the transmitting device from a database of patterns. We demonstrate that the patterns produced by different models of smartphones are easily different enough to be identified. Our measurements are repeatably measurable using RSS with commercial-off-theshelf hardware. We then use simulations to show the success of our method as a classifier.


Wireless Radiation Patterns, Device Fingerprinting, Identification.