《Tab.2 Detection result of different detection methods》

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《基于网络行为特征与Dezert-Smarandache理论的P2P僵尸网络检测（英文）》

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From Tab.2 and Tab.3，only using the param eter HD and only using the param eter HE result in the high false negative and false positive rate，respectively.Due to the com plexity and variability of the features of P2 P botnet，a single netw ork feature is not enough to accurately describe the details of the traffic changes.Therefore，the data fusion algorithm of the decision level is em ployed to solve the problem in the proposed m ethod.These m easures increase the accuracy of the P2 P botnet detection to som e degree.1 018（763）in Tab.2 denotes that the detection m ethod detects 1 018 tim es of attack in total w ith763 correct.