CODDULM:一种在被动DNS流量中检测DGA C&C域的方法

Chunyu Han, Yongzheng Zhang
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引用次数: 5

摘要

域名作为互联网的重要组成部分之一,利用域名进行的恶意行为越来越多,如垃圾邮件、僵尸网络、网络钓鱼等。DGA (Domain Generation Algorithm,域生成算法)是DNS技术的一种,在僵尸网络中被广泛用于域流量。在本文中,我们提出了一种称为CODDULM(使用词法特征和稀疏矩阵的Dga检测的C&c域)的方法。首先在被动DNS流量中查找nxdomain(不存在的域),定位可疑的被感染主机。其次,根据可疑感染主机的词法特征选择DGA域;最后,通过支持向量机(SVM)分类器发现DGA C&C(命令与控制)域。在本文的最后,通过实验验证了该方法的有效性和较高的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CODDULM: An approach for detecting C&C domains of DGA on passive DNS traffic
Domain plays an important role as one of the components on the Internet, so more and more malicious behavior has been conducted by using domains, such as spam, botnet, phishing and the like. DGA (Domain Generation Algorithm), one kind of DNS technology, has been used by domain-flux commonly in botnets. In this paper, we propose a method called CODDULM (C&c domains Of Dga Detection Using Lexical feature and sparse Matrix). Firstly, it finds the NXDomains (Non-existent domains) on the passive DNS traffic to locate the suspicious infected hosts. Secondly, it selects DGA domains by lexical features according to suspicious infected hosts. Lastly, it discovers DGA C&C (Command and Control) domains through SVM (Support Vector Machine algorithm) classifier. At the end of this paper, we conduct the experiment to verify the effect of the method and the high accuracy of it.
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