Themis:一种检测混合算法生成域的新方法

Chao Zheng, Qian Qiang, Tianning Zang, Wen-Han Chao, Yuan Zhou
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引用次数: 1

摘要

随着DGA (Domain Generation Algorithm)检测技术和系统的日益复杂,出现了越来越多的算法生成域(AGD)类型:基于字典的AGD、基于哈希的AGD等。本文将深度学习应用于网络安全领域,提出了一种轻量级的AGD检测方法Themis,该方法可以通过域名字符串将域名分为合法域名和AGD。Themis将WordNet和GRU结合起来,捕捉合法域名和AGD的不同特征进行分类。与现有技术相比,Themis有两个不同之处:1)Themis是第一种检测混合AGD(基于算术和基于字典)的方法;2) Themis在检测未知AGD方面表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Themis: A Novel Detection Approach for Detecting Mixed Algorithmically Generated Domains
As DGA (Domain Generation Algorithm) detection technologies and systems become more and more complex, more types of AGD (Algorithmically Generated Domain) appear: Dictionary-based AGD, Hash-based AGD, etc. This paper applies deep learning to the field of network security, proposes a lightweight AGD detection approach, Themis, which can classify domain names into legitimate domain names or AGDs through domain name strings. Themis combines WordNet and GRU to capture the different characteristics of legitimate domain name and AGD for classification. Compared with the prior art, Themis has two differences: 1) Themis is the first approach to detect mixed AGD (Arithmetic-based and Dictionary-based); 2) Themis performs well in detecting unknowns AGD.
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