检测多网络主机的DDoS攻击

Konstantinos F. Xylogiannopoulos, P. Karampelas, R. Alhajj
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引用次数: 4

摘要

低安全性物联网设备的激增扩大了恶意用户可以利用的武器范围,以便以新的方式攻击合法服务。近年来,除了非常大容量的分布式拒绝服务攻击外,还发现了智能bot网络发起的针对网络中多台主机的慢速慢速攻击。然而,即使这些攻击在一开始看起来是“无辜的”,但它们在网络中产生了巨大的流量,而传统的DDoS攻击检测方法实际上并没有检测到它们。在本章中,我们提出了一种先进的模式检测方法,通过对网络中所有主机的流量进行监控,实时收集和分类所有传入的流量,检测出正在发展的慢速低流量DDoS攻击。对真实数据集的实验分析提供了关于该方法有效性的有用见解,不仅可以识别主要攻击源,还可以识别产生低流量的次要来源,通过多个主机进行攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting DDoS Attacks on Multiple Network Hosts
The proliferation of low security internet of things devices has widened the range of weapons that malevolent users can utilize in order to attack legitimate services in new ways. In the recent years, apart from very large volumetric distributed denial of service attacks, low and slow attacks initiated from intelligent bot networks have been detected to target multiple hosts in a network in a timely fashion. However, even if the attacks seem to be “innocent” at the beginning, they generate huge traffic in the network without practically been detected by the traditional DDoS attack detection methods. In this chapter, an advanced pattern detection method is presented that is able to collect and classify in real time all the incoming traffic and detect a developing slow and low DDoS attack by monitoring the traffic in all the hosts of the network. The experimental analysis on a real dataset provides useful insights about the effectiveness of the method by identifying not only the main source of attack but also secondary sources that produce low traffic, targeting though multiple hosts.
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