论文标题
“猜谁？”以数据为中心的大规模数据以浏览器指纹用于Web身份验证的充分性研究
"Guess Who ?" Large-Scale Data-Centric Study of the Adequacy of Browser Fingerprints for Web Authentication
论文作者
论文摘要
浏览器指纹包括从Web浏览器收集属性以构建浏览器指纹。在这项工作中，我们将浏览器指纹作为身份验证因子的充分性评估在4,145,408个指纹的数据集上，该数据集由216个属性组成。它是从一系列一般浏览器人群中收集的。我们将浏览器指纹的属性确定，正式化和评估是可用且实际的身份验证因素。我们显着评估了它们的独特性，它们的稳定性，时间，收集时间以及记忆中的大小。我们表明，考虑到216个指纹属性的大表面导致1,989,365个浏览器的单位率为81％。此外，已知浏览器指纹会发展，但是我们观察到，在连续的指纹之间，超过90％的属性在将近6个月后保持不变。指纹也负担得起。平均而言，它们重十二千元，并在几秒钟内收集。我们得出的结论是，浏览器指纹是一个有希望的其他Web身份验证因素。
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.
