Identification of malicious web pages through analysis of underlying DNS and web server relationships

C. Seifert, I. Welch, P. Komisarczuk, C. Aval, B. Endicott-Popovsky
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引用次数: 37

Abstract

Malicious Web pages that launch drive-by-download attacks on Web browsers have increasingly become a problem in recent years. High-interaction client honeypots are security devices that can detect these malicious Web pages on a network. However, high-interaction client honeypots are both resource-intensive and unable to handle the increasing array of vulnerable clients. This paper presents a novel classification method for detecting malicious Web pages that involves inspecting the underlying server relationships. Because of the unique structure of malicious front-end Web pages and centralized exploit servers, merely counting the number of domain name extensions and Domain Name System (DNS) servers used to resolve the host names of all Web servers involved in rendering a page is sufficient to determine whether a Web page is malicious or benign, independent of the vulnerable Web browser targeted by these pages. Combining high-interaction client honeypots and this new classification method into a hybrid system leads to performance improvements.
通过分析底层DNS和web服务器关系来识别恶意网页
近年来,对Web浏览器发起“驱动下载”攻击的恶意网页日益成为一个问题。高交互性客户机蜜罐是可以检测网络上这些恶意Web页面的安全设备。然而,高交互客户端蜜罐是资源密集型的,并且无法处理越来越多的易受攻击的客户端。本文提出了一种检测恶意网页的新型分类方法,该方法包括检查底层服务器关系。由于恶意前端Web页面和集中式利用服务器的独特结构,仅计算用于解析呈现页面所涉及的所有Web服务器的主机名的域名扩展和域名系统(DNS)服务器的数量就足以确定Web页面是恶意的还是良性的,而与这些页面所针对的易受攻击的Web浏览器无关。将高交互客户端蜜罐和这种新的分类方法结合到一个混合系统中可以提高性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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