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Investigating Real-Time Entropy Features of DDoS Attack Based on Categorized Partial-Flows

机译:基于分类局部流的DDoS攻击实时熵特征研究

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With the advent of IoT devices and exponential growth of nodes on the internet, computer networks are facing new challenges, with one of the more important ones being DDoS attacks. In this paper, new features to detect initiation and termination of DDoS attacks are investigated. The method to extract these features is devised with respect to some openflowbased switch capabilities. These features provide us with a higher resolution to view and process packet count entropies, thus improving DDoS attack detection capabilities. Although some of the technical assumptions are based on SDN technology and openflow protocol, the methodology can be applied in other networking paradigms as well.
机译:随着物联网设备的出现和互联网上节点的指数增长,计算机网络面临着新的挑战,其中最重要的挑战之一就是DDoS攻击。本文研究了用于检测DDoS攻击的发起和终止的新功能。针对某些基于开放流的交换功能,设计了提取这些功能的方法。这些功能为我们提供了更高的分辨率,以查看和处理数据包计数熵,从而提高了DDoS攻击检测能力。尽管一些技术假设是基于SDN技术和开放流协议的,但该方法也可以应用于其他网络范例。

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