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Supervised classification of packets coming from a HTTP botnet

机译:对来自HTTP僵尸网络的数据包进行监督分类

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摘要

The posibilities that the management of a vast amount of computers and/or networks offer, is attracting an increasing number of malware writers. In this document, the authors propose a methodology thought to detect malicious botnet traffic, based on the analysis of the packets flow that circulate in the network. This objective is achieved by means of the parametrization of the static characteristics of packets, which are lately analysed using supervised machine learning techniques focused on traffic labelling so as to face proactively to the huge volume of information nowadays filters work with.
机译:大量计算机和/或网络的管理所提供的可能性正在吸引越来越多的恶意软件编写者。在本文档中,作者基于对网络中流通的数据包流的分析,提出了一种用于检测恶意僵尸网络流量的方法。该目的是通过对数据包静态特征进行参数化来实现的,该参数最近被使用针对流量标签的有监督的机器学习技术进行了分析,从而可以主动应对当今与过滤器一起工作的大量信息。

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