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首页> 外文期刊>International journal of critical infrastructure >Neuro-fuzzy-based clustering of DDoS attack detection in the network
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Neuro-fuzzy-based clustering of DDoS attack detection in the network

机译：网络中基于神经模糊的DDoS攻击检测群集

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摘要

The detection system developed for wired networks cannot be deployed in wireless networks due to the difference between the two types of networks. The data transmission of the wired network is a standard physical routing. However, the data stream routing of wireless network are based on radio signals with a variety of problems of evolution. The attacker's packet header data are acknowledged with a port number, option field parameters and IP address. The anomalies detection is carried out at a regular interval to monitor the traffic analysed through statistical variance. The change detection detects the statistical variance of the traffic volume. The results obtained from the proposed system are compared with the existing attack detection systems with the propagation delay metric. It shows a reduction of nearly 10% and an improvement of 13% average throughput.
机译：由于两种类型的网络之间的差异，为有线网络开发的检测系统无法部署在无线网络中。有线网络的数据传输是标准的物理路由。但是，无线网络的数据流路由是基于无线电信号的，存在各种演进问题。通过端口号，选项字段参数和IP地址确认攻击者的数据包头数据。定期检测异常，以监视通过统计方差分析的流量。变化检测检测交通量的统计方差。从提议的系统获得的结果与具有传播延迟度量的现有攻击检测系统进行了比较。它显示平均吞吐量减少了近10％，提高了13％。

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