基于流量日志特征的APT攻击检测方法

Xingjie Huang, Beibei Su, Ru Zhang, Feiyu Chen, Jinmeng Zhao, Yating Gao
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引用次数: 1

摘要

APT(高级持续威胁)攻击通常可以通过躲避IDS系统的检测来隐藏攻击过程。本文提出了一种利用匿名数据集检测APT攻击中C2阶段网络行为的模型。针对C2域名访问记录,提出了基于DNS行为规则的多种特征,并将这些特征与流量特征融合。将在大型组织中收集的数据与仿真数据相结合进行实验。实验结果表明,本文方法具有大数据下检测APT攻击的能力,能够检测出疑似被感染的主机。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
APT Attack Detection Method Based on Traffic Log Features
APT (Advanced Persistent Threat) attack can generally hide the attack process by evading the detection of the IDS system. This paper proposes a detection model for C2 stage network behavior in APT attacks using anonymized datasets. For C2 domain name access records, a number of features based on DNS behavior rules are proposed, and these features are fused with traffic features. Experiments are carried out by combining the data collected in a large-scale organization with the simulation data. The experiments result shows that the method in this paper has the ability to detect APT attacks under large data, and can detect suspected infected hosts.
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