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"Guess Who ?" Large-Scale Data-Centric Study of the Adequacy of Browser Fingerprints for Web Authentication

Abstract : 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.
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Submitted on : Tuesday, June 22, 2021 - 5:22:31 PM
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Guess Who - Large-Scale Data-C...
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Nampoina Andriamilanto, Tristan Allard, Gaetan Le Guelvouit. "Guess Who ?" Large-Scale Data-Centric Study of the Adequacy of Browser Fingerprints for Web Authentication. International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), Jul 2020, Lodz, Poland. pp.161-172, ⟨10.1007/978-3-030-50399-4_16⟩. ⟨hal-02611624v4⟩



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