机器学习在僵尸网络检测中的作用

Sean T. Miller, Curtis Busby-Earle
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引用次数: 32

摘要

在过去的十到十五年里,僵尸网络已经引起了全世界研究人员的关注。人们已经付出了大量的努力来开发能够有效地检测僵尸网络存在的系统。这个独特的问题看到研究人员应用机器学习(ML)来解决这个问题。在本文中,我们简要概述了不同的机器学习(ML)方法及其在僵尸网络检测中的作用。本文的主要目的是明确定义不同的机器学习方法在僵尸网络检测中的作用。清楚地了解这些角色对于开发有效和高效的实时在线检测方法和更健壮的模型至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The role of machine learning in botnet detection
Over the past ten to fifteen years botnets have gained the attention of researchers worldwide. A great deal of effort has been given to developing systems that would efficiently and effectively detect the presence of a botnet. This unique problem saw researchers applying machine learning (ML) to solve this problem. In this paper we provide a brief overview the different machine learning (ML) methods and the part they play in botnet detection. The main aim of this paper is to clearly define the role different ML methods play in Botnet detection. A clear understanding of these roles are critical for developing effective and efficient real-time online detection approaches and more robust models.
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