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Include Me Out: In-Browser Detection of Malicious Third-Party Content Inclusions

机译:包括我:浏览器检测恶意第三方内容包含夹杂物

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Modern websites include various types of third-party content such as JavaScript, images, stylesheets, and Flash objects in order to create interactive user interfaces. In addition to explicit inclusion of third-party content by website publishers, ISPs and browser extensions are hijacking web browsing sessions with increasing frequency to inject third-party content (e.g., ads). However, third-party content can also introduce security risks to users of these websites, unbeknownst to both website operators and users. Because of the often highly dynamic nature of these inclusions as well as the use of advanced cloaking techniques in contemporary malware, it is exceedingly difficult to preemptively recognize and block inclusions of malicious third-party content before it has the chance to attack the user's system. In this paper, we propose a novel approach to achieving the goal of preemptive blocking of malicious third-party content inclusion through an analysis of inclusion sequences on the Web. We implemented our approach, called EXCISION, as a set of modifications to the Chromium browser that protects users from malicious inclusions while web pages load. Our analysis suggests that by adopting our in-browser approach, users can avoid a significant portion of malicious third-party content on the Web. Our evaluation shows that EXCISION effectively identifies malicious content while introducing a low false positive rate. Our experiments also demonstrate that our approach does not negatively impact a user's browsing experience when browsing popular websites drawn from the Alexa Top 500.
机译:现代网站包括各种类型的第三方内容,如JavaScript,图像,样式表和闪存对象,以便创建交互式用户界面。除了通过网站发布者明确包含第三方内容,ISP和浏览器扩展是劫持Web浏览会话,随着频率的增加来注入第三方内容(例如,广告)。但是,第三方内容也可以向这些网站的用户介绍安全风险,对网站运营商和用户不知道。由于这些夹杂物的往往具有高度动态性质以及在当代恶意软件中使用先进的粘附技术,因此在有机会攻击用户的系统之前,它非常难以先发制人识别和阻止恶意的第三方内容的含量。在本文中,我们提出了一种新颖的方法,通过对网上的包涵序列分析来实现验证恶意第三方内容夹杂物的目标。我们实现了我们的方法,称为切除,作为对铬浏览器的一组修改,在网页加载时保护用户免受恶意夹杂物。我们的分析表明,通过采用我们的浏览器方法,用户可以避免网络上的重要部分恶意第三方内容。我们的评价表明,切除有效地识别恶意内容,同时引入低误率。我们的实验还表明,我们的方法在浏览从Alexa Top 500绘制的流行网站时,我们的方法不会对用户的浏览体验产生负面影响。

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