摘要
研究P2P流量的识别对于P2P网络的管理具有十分重要的意义,针对当前P2P流量的识别方法存在的误差大,识别结果不稳定等缺陷,为了改善P2P流量的识别效果,提出神经网络的P2P流量的识别方法。首先采集P2P流量数据,并对其进行预处理,建立P2P流量的识别样本集合;然后根据P2P流量的识别学习,神经网络进行训练,建立P2P流量的识别模型;最后采用VC++编程实现P2P流量的识别实验。实验结果表明,基于神经网络的P2P流量识别精度高,识别结果十分稳定,且P2P流量的识别效率高,可以对P2P流量进行在线管理,具有较高的实际应用价值。
The research of P2P traffic identification is very important for the management of P2P network. Aiming at the defects of the current identification methods of P2P traffic, such as large error and unstable identification results, in order to improve the identification effect of P2P traffic, an identification method of P2P traffic based on neural network is proposed. Firstly, the data of P2P traffic are collected and preprocessed to establish the identification sample set of P2P traffic. Then, according to the identification learning of P2P traffic, neural network is trained to establish the identification model of P2P traffic. Finally, VC++ is used to program, and experiments are completed. The results show that the identification accuracy of P2P traffic based on neural network is high, the identification result is very stable, and the identification efficiency of P2P traffic is high. It can manage P2P traffic online and has high practical application value.
作者
王玮
WANG Wei(Basic Teaching Department,Shanxi Art Vocational College,Xi’an 710054,China)
出处
《微型电脑应用》
2021年第3期111-113,共3页
Microcomputer Applications
关键词
P2P网络
流量数据集
神经网络
预处理
识别实验
P2P network
traffic data set
neural network
preprocessing
identification experiment