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Detecting and Preventing Drive-By Download Attack via Participative Monitoring of the Web

机译:通过Web的参与性监视来检测和防止按驱动下载下载攻击

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Drive-by Download Attack (DBD) is one of the major threats on the web infrastructure. DBD attacks are triggered by user access to a malicious website and force users to download malware by exploiting the vulnerabilities of web browsers or plugins. Malicious websites are ephemeral. Therefore, it is necessary to gather fresh information related to malicious activities to detect and prevent such attacks. In this paper, we propose a framework that combats with DBD attacks with users' voluntary monitoring of the web. This framework tackles the two issues: ways to obtain up-to-date information related malicious activities and ways to provide up-to-date information to the world. The framework aims to realize a security ecosystem: users actively offer information about their activities on the web (e.g. access URL, download contents), and security analysts inspect the information to detect new threats and devise countermeasures for any new threats and then provide the countermeasures to users as feedback. The framework consists of sensors located on the user side and a centralized center located on the network side. Sensors are deployed in the web browser, in web proxies, and DNS servers. Sensors monitors the access URLs download contents, the method of triggering the link events (e.g. mouse click, move, redirected by the server), then the sensors report the data to the center. The center analyzes the data, derives the statistical data and the web link structure, and detects new threats by facilitating the characteristics of malicious web pages. This paper also shows a real world example that demonstrates the potential of our framework. The example implies that our focus on the change of the web link structure can detect illegal falsification of web pages. Our framework can obtain long-term data on how many hosts users are forced to access by the access of a web page, so we believe that our framework can distinguish legitimate changes in web pages with compromised changes.
机译:偷渡式下载攻击(DBD)是Web基础架构上的主要威胁之一。用户访问恶意网站会触发DBD攻击,并通过利用Web浏览器或插件的漏洞迫使用户下载恶意软件。恶意网站是短暂的。因此,有必要收集与恶意活动有关的最新信息以检测和防止此类攻击。在本文中,我们提出了一个通过用户自愿监视Web来与DBD攻击作斗争的框架。该框架解决了两个问题:获取与恶意活动有关的最新信息的方法以及向全世界提供最新信息的方法。该框架旨在实现一个安全生态系统:用户在网络上积极提供有关其活动的信息(例如访问URL,下载内容),安全分析人员检查该信息以检测新威胁并针对任何新威胁制定对策,然后提供对策。给用户作为反馈。该框架由位于用户端的传感器和位于网络端的集中式中心组成。传感器部署在Web浏览器,Web代理和DNS服务器中。传感器监视访问URL的下载内容,触发链接事件的方法(例如,鼠标单击,移动,由服务器重定向),然后传感器将数据报告给中心。该中心分析数据,导出统计数据和Web链接结构,并通过促进恶意网页的特征来检测新威胁。本文还显示了一个真实的示例,展示了我们框架的潜力。该示例表明,我们对更改Web链接结构的关注可以检测到网页的非法篡改。我们的框架可以获取有关通过访问网页迫使用户访问多少主机的长期数据,因此我们认为,我们的框架可以区分网页中的合法更改和受到破坏的更改。

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