Resumen (Español): se puede identificar a un usuario de acuerdo al hardware que esta utilizando mediante llamadas a WebGL haciendo de esta forma que la huella identificatoria del usuario sea «cross browser» es decir «lo siga» independiente del navegador que utilice.
Generando de esta forma una nueva técnica de «Web Browsing fingerprinting».
Abstract—In this paper, we propose a browser fingerprinting technique that can track users not only within a single browser but also across different browsers on the same machine. Specifically, our approach utilizes many novel OS and hardware level features, such as those from graphics cards, CPU, and installed writing scripts. We extract these features by asking browsers to perform tasks that rely on corresponding OS and hardware functionalities.
Our evaluation shows that our approach can successfully identify 99.24% of users as opposed to 90.84% for state of theart on single-browser fingerprinting against the same dataset.
Further, our approach can achieve higher uniqueness rate than the only cross-browser approach in the literature with similar stability.
