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Using HTML5 to Prevent Detection of Drive-by-Download Web Malware

机译:使用HTmL5防止检测按下载驱动的Web恶意软件

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摘要

The web is experiencing an explosive growth in the last years. Newtechnologies are introduced at a very fast-pace with the aim of narrowing thegap between web-based applications and traditional desktop applications. Theresults are web applications that look and feel almost like desktopapplications while retaining the advantages of being originated from the web.However, these advancements come at a price. The same technologies used tobuild responsive, pleasant and fully-featured web applications, can also beused to write web malware able to escape detection systems. In this article wepresent new obfuscation techniques, based on some of the features of theupcoming HTML5 standard, which can be used to deceive malware detectionsystems. The proposed techniques have been experimented on a reference set ofobfuscated malware. Our results show that the malware rewritten using ourobfuscation techniques go undetected while being analyzed by a large number ofdetection systems. The same detection systems were able to correctly identifythe same malware in its original unobfuscated form. We also provide some hintsabout how the existing malware detection systems can be modified in order tocope with these new techniques.
机译:近年来,网络正经历爆炸性的增长。引入新技术的步伐非常快,其目的是缩小基于Web的应用程序与传统桌面应用程序之间的差距。结果是,Web应用程序在外观和感觉上几乎类似于桌面应用程序,同时保留了源于Web的优点。但是,这些进步是有代价的。用于构建响应式,令人愉悦且功能齐全的Web应用程序的技术也可以用来编写能够逃脱检测系统的Web恶意软件。在本文中,我们将基于即将到来的HTML5标准的一些功能介绍新的混淆技术,该技术可用于欺骗恶意软件检测系统。所提议的技术已经在模糊软件的参考集上进行了实验。我们的结果表明,使用我们的混淆技术重写的恶意软件在被大量检测系统分析时未被发现。相同的检测系统能够以原始的原始形式正确识别相同的恶意软件。我们还提供一些有关如何修改现有恶意软件检测系统以应对这些新技术的提示。

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