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A static approach to detect drive-by-download attacks on webpages

机译:一种静态方法,可检测网页上的按下载下载攻击

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摘要

Today, Internet has become another life to most of us. Other than a basic communication network, Internet has developed to be an interconnected information source, enabling different forms of social interactions and marketing. Cyber criminals use computer as a weapon to enrich themselves by taking undue advantage of legitimate sites. A serious threat in web browsing is that the attackers use drive-by-download exploits by embedding malicious codes into web pages. When user with vulnerable browser visits this page, browser gets compromised. Here a static method is discussed to extract useful information from webpage and analyses it for the presence of malicious content. Based on the features extracted from the HTML contents of a web page, different classifiers are implemented and tested in MATLAB and their detection accuracies are compared. Classifying algorithms of WEKA are also used for the study and their performance is compared.
机译:今天,互联网已经成为我们大多数人的另一种生活。除了基本的通信网络外,Internet已发展成为一个互连的信息源,可以实现各种形式的社交互动和营销。网络罪犯利用计算机作为武器,通过过度利用合法站点来丰富自己。 Web浏览中的一个严重威胁是,攻击者通过将恶意代码嵌入网页来使用通过下载驱动的漏洞。当浏览器存在漏洞的用户访问此页面时,浏览器就会受到攻击。这里讨论了一种静态方法,用于从网页中提取有用的信息并分析其中是否存在恶意内容。基于从网页的HTML内容中提取的功能,在MATLAB中实现并测试了不同的分类器,并比较了它们的检测精度。 WEKA的分类算法也用于研究,并比较了它们的性能。

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