基于级联森林集的检测域生成算法

Xianrong Song, Haoliang Sun, Hong Zhang, Meng Zhang
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引用次数: 0

摘要

在僵尸网络中,攻击者经常使用域变换来隐藏通信通道。领域生成算法(DGA)是一种常用的领域磁通技术。每个bot使用DGA生成大量域名,其中一个域名将被botmaster注册为映射到C&C服务器的域名。大量的DGA域名会给保安人员带来麻烦。在本文中,我们提出了一种称为Minos的DGA检测方法。该方法通过使用级联森林算法分析域名的构词法来检测dga生成的域名。Minos的关键见解是,域名由音节或首字母缩写组成,便于阅读,n-gram通常可以表示这两种形式。实验结果表明,Minos可以准确识别由DGAs生成的域名,准确率为93.8%,召回率为93.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting Domain Generation Algorithms Based on Cascade Foresets
In a botnet, the attacker often uses domain fluxing to hide communication channel. Domain Generation Algorithm (DGA) is a kind of technique which is usually utilized by domain fluxing. Each bot uses a DGA to generate plenty of domain names and one of them will be registered by the botmaster as the domain name mapping to the C&C server. The security personnel will be in trouble with a large number of DGA domain names. In this paper, we propose a DGA detection approach called Minos. This approach detects DGA-generated domain names by analyzing the word-formation of domain names with the cascaded forest algorithm. The key insight of Minos is that domain names are made up of syllables or acronyms for easy reading, and n-grams can generally represent both of them. Our experimental results show that Minos can accurately identify domain names generated by DGAs with a precision of 93.8% and a recall rate of 93.5%.
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