An Automated Approach for Complementing Ad Blockers’ Blacklists
An Automated Approach for Complementing Ad Blockers’ Blacklists
复制标题
补充广告拦截器黑名单的自动化方法
DOI：
10.1515/popets-2015-0018
复制
发表时间：
2015
影响因子：
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通讯作者：
Vincent Lenders
中科院分区：
文献类型：
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作者：
David Gugelmann;Markus Happe;Bernhard Ager;Vincent Lenders
摘要Web中的隐私已成为一个主要问题，导致各种工具的流行使用，以阻止跟踪服务。这些工具中的大多数依赖于手动维护的黑名单，需要保持最新以有效保护Web用户的隐私。跟上当今快速发展的广告和分析领域的步伐是一项挑战。为了支持黑名单维护者与此任务，我们确定了一组Web流量的功能，用于识别privacyinvasive服务。基于这些功能，我们开发了一种自动方法，学习现有黑名单列出的广告和分析服务的属性，并提出新的服务列入黑名单。我们评估我们的技术对校园网络的真实的流量痕迹，并发现在200个新的隐私侵入Web服务，没有列出最流行的Firefox插件Adblock Plus的顺序。建议的Web流量功能很容易得到，允许分布式实现我们的方法。
Abstract Privacy in the Web has become a major concern resulting in the popular use of various tools for blocking tracking services. Most of these tools rely on manually maintained blacklists, which need to be kept up-to-date to protect Web users’ privacy efficiently. It is challenging to keep pace with today’s quickly evolving advertisement and analytics landscape. In order to support blacklist maintainers with this task, we identify a set of Web traffic features for identifying privacyintrusive services. Based on these features, we develop an automatic approach that learns the properties of advertisement and analytics services listed by existing blacklists and proposes new services for inclusion on blacklists. We evaluate our technique on real traffic traces of a campus network and find in the order of 200 new privacy-intrusive Web services that are not listed by the most popular Firefox plug-in Adblock Plus. The proposed Web traffic features are easy to derive, allowing a distributed implementation of our approach.