典型文献
An approach for detecting LDoS attack based on cloud model
文献摘要：
Cybersecurity has always been the focus of Internet research.An LDoS attack is an intelligent type of DoS attack,which reduces the quality of network service by periodically sending high-speed but short-pulse attack traffic.Because of its concealment and low average rate,the traditional DoS attack detection methods are challenging to be effective.The existing LDoS attack detection methods generally have the problems of high FPR and FNR.A cloud model-based LDoS attack detec-tion method is proposed,and a classifier based on SVM is used to train and classify the feature parameters.The detection method is verified and tested in the NS2 simulation platform and Test-bed network environment.Compared with the existing research results,the proposed method requires fewer samples,and it has lower FPR and FNR.
文献关键词：
中图分类号：
作者姓名：
Wei SHI;Dan TANG;Sijia ZHAN;Zheng QIN;Xiyin WANG
作者机构：
College of Computer Science and Electronic Engineering,Hunan University,Changsha 410082,China
文献出处：
引用格式：
[1]Wei SHI;Dan TANG;Sijia ZHAN;Zheng QIN;Xiyin WANG-.An approach for detecting LDoS attack based on cloud model)[J].计算机科学前沿,2022(06):117-128
A类：
LDoS
B类：
An,approach,detecting,attack,cloud,model,Cybersecurity,has,always,been,focus,Internet,research,intelligent,type,which,reduces,quality,network,service,by,periodically,sending,high,speed,but,short,pulse,traffic,Because,its,concealment,average,rate,traditional,detection,methods,challenging,effective,existing,generally,have,problems,FPR,FNR,proposed,classifier,used,train,classify,feature,parameters,verified,tested,NS2,simulation,platform,Test,bed,environment,Compared,results,requires,fewer,samples,lower
AB值：
0.531644
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