Block Me If You Can: A Large-Scale Study of Tracker-Blocking Tools
Block Me If You Can: A Large-Scale Study of Tracker-Blocking Tools
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DOI：
10.1109/eurosp.2017.26
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发表时间：
2017-04
期刊：
影响因子：
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通讯作者：
Georg Merzdovnik;Markus Huber;D. Buhov;Nick Nikiforakis;S. Neuner;Martin Schmiedecker;E. Weippl
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文献类型：
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作者：
Georg Merzdovnik;Markus Huber;D. Buhov;Nick Nikiforakis;S. Neuner;Martin Schmiedecker;E. Weippl
在本文中，我们对第三方跟踪拦截程序的有效性进行了大规模的量化。首先，我们分析了各种先进的阻塞解决方案的体系结构，并讨论了每种方法的优缺点。其次，我们对流行的跟踪器拦截工具的有效性进行了两部分的测量研究。我们的分析量化了针对10多万个流行网站和10,000个流行Android应用程序上的跟踪器提供的保护。我们为追踪者和拦截工具开发者之间正在进行的军备竞赛提供了新的见解，以及哪些工具在什么情况下能取得最好的结果。其中，我们发现基于规则的浏览器扩展比基于学习的浏览器扩展性能更好，足迹更小的跟踪器在避免被阻止方面更成功，CDN对跟踪器阻止工具的未来构成了重大威胁。总体而言，本文的贡献不仅提供了迄今为止关于追踪器拦截工具有效性的最大规模的研究，而且还突出了第三方跟踪最紧迫的挑战和隐私问题，从而推动了网络隐私领域的发展。
In this paper, we quantify the effectiveness of third-party tracker blockers on a large scale. First, we analyze the architecture of various state-of-the-art blocking solutions and discuss the advantages and disadvantages of each method. Second, we perform a two-part measurement study on the effectiveness of popular tracker-blocking tools. Our analysis quantifies the protection offered against trackers present on more than 100,000 popular websites and 10,000 popular Android applications. We provide novel insights into the ongoing arms race between trackers and developers of blocking tools as well as which tools achieve the best results under what circumstances. Among others, we discover that rule-based browser extensions outperform learning-based ones, trackers with smaller footprints are more successful at avoiding being blocked, and CDNs pose a major threat towards the future of tracker-blocking tools. Overall, the contributions of this paper advance the field of web privacy by providing not only the largest study to date on the effectiveness of tracker-blocking tools, but also by highlighting the most pressing challenges and privacy issues of third-party tracking.