"Guess Who ?" Large-Scale Data-Centric Study of the Adequacy of Browser Fingerprints for Web Authentication
This addresses web authentication security by evaluating browser fingerprints as a practical factor, though it is incremental as it builds on existing fingerprinting methods.
The study assessed browser fingerprints as a web authentication factor using a dataset of 4,145,408 fingerprints with 216 attributes, finding an 81% uniqueness rate and over 90% attribute stability over 6 months.
Browser fingerprinting consists in collecting attributes from a web browser to build a browser fingerprint. In this work, we assess the adequacy of browser fingerprints as an authentication factor, on a dataset of 4,145,408 fingerprints composed of 216 attributes. It was collected throughout 6 months from a population of general browsers. We identify, formalize, and assess the properties for browser fingerprints to be usable and practical as an authentication factor. We notably evaluate their distinctiveness, their stability through time, their collection time, and their size in memory. We show that considering a large surface of 216 fingerprinting attributes leads to an unicity rate of 81% on a population of 1,989,365 browsers. Moreover, browser fingerprints are known to evolve, but we observe that between consecutive fingerprints, more than 90% of the attributes remain unchanged after nearly 6 months. Fingerprints are also affordable. On average, they weigh a dozen of kilobytes, and are collected in a few seconds. We conclude that browser fingerprints are a promising additional web authentication factor.