检测P2P僵尸网络的机器学习算法行为分析

Shree Garg, Ankush Kumar Singh, A. Sarje, S. K. Peddoju
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引用次数: 31

摘要

僵尸网络已经成为互联网上一个强大的威胁,因为它被用来实施网络犯罪。在本文中,我们分析了一些机器学习技术来检测点对点(P2P)僵尸网络。由于P2P僵尸网络的检测是一个广泛未开发的领域,因此我们对其进行了重点研究。我们实验了不同的机器学习(ML)算法,通过选择网络流量的显著特征来比较它们从正常流量中分类僵尸网络流量的能力。在包含各种P2P僵尸网络痕迹的数据集上进行了实验。最后给出了不同机器学习算法在不同度量上的结果和权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Behaviour analysis of machine learning algorithms for detecting P2P botnets
Botnets have emerged as a powerful threat on the Internet as it is being used to carry out cybercrimes. In this paper, we have analysed some machine learning techniques to detect peer to peer (P2P) botnets. As the detection of P2P botnets is widely unexplored area, we have focused on it. We experimented with different machine learning (ML) algorithms to compare their ability to classify the botnet traffic from the normal traffic by selecting distinguishing features of the network traffic. Experiments are performed on the dataset containing the traces of various P2P botnets. Results and tradeoffs obtained of different ML algorithms on different metrics are presented at the end of the paper.
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