The Elephant in the Background: A Quantitative Approachto Empower Users Against Web Browser Fingerprinting

Julian Fietkau, Kashjap Thimmaraju, Felix Kybranz, Sebastian Neef, Jean-Pierre Seifert
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引用次数: 6

Abstract

Tracking users is a ubiquitous practice on the web today. User activity is recorded and analyzed on a large scale to create personalized products, forecast future behavior, and prevent online fraud. While HTTP cookies have been the weapon of choice so far, new and more pervasive techniques such as browser fingerprinting are gaining traction. This paper describes how users can be empowered against fingerprinting by showing them when, how, and who is tracking them. To this end, we conduct a systematic analysis of various fingerprinting tools to create FPMON: a browser extension to measure and rate fingerprinting activity on any website in real-time. With FPMON, we evaluate the 10k most popular websites to i) study the pervasiveness of fingerprinting; ii) review the latest countermeasures; and iii) identify the networks that foster the use of fingerprinting. Our evaluations reveal that i) fingerprinters subvert privacy regulations; ii) they are present on privacy-sensitive websites (insurance, finances, NGOs); and iii) current countermeasures cannot sufficiently protect users. Hence, we publish FPMON as a free browser extension to empower users against this growing threat.
背景中的大象:一种授权用户对抗Web浏览器指纹的定量方法
在今天的网络上,跟踪用户是一种无处不在的做法。大规模记录和分析用户活动,以创建个性化产品,预测未来行为,防止在线欺诈。虽然到目前为止,HTTP cookie一直是首选的武器,但浏览器指纹识别等新的、更普遍的技术正在获得关注。本文描述了如何通过向用户显示何时、如何以及谁在跟踪他们来授权用户反对指纹识别。为此,我们对各种指纹识别工具进行了系统的分析,以创建FPMON:一个浏览器扩展,用于实时测量和评估任何网站上的指纹识别活动。利用FPMON,我们评估了1万个最受欢迎的网站,以i)研究指纹识别的普遍性;Ii)审查最新的对策;iii)识别助长使用指纹识别的网络。我们的评估显示,1)指纹识别颠覆了隐私法规;ii)出现在隐私敏感网站(保险、金融、非政府组织);当前的对策不能充分保护用户。因此,我们发布FPMON作为一个免费的浏览器扩展,以授权用户对抗这种日益增长的威胁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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