| 一种基于SVM的P2P流量检测方法研究 |
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| 引用本文： | 姜伟,王春枝,罗宏芳,陈宏伟.一种基于SVM的P2P流量检测方法研究[J].湖北工业大学学报,2010,25(2):48-50. |
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| 作者姓名： | 姜伟 王春枝 罗宏芳 陈宏伟 |
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| 作者单位： | 湖北工业大学计算机学院,湖北,武汉,430068 |
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| 基金项目： | 湖北省自然科学基金，武汉市青年科技晨光计划项目 |
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| 摘 要： | 提出了一种基于SVM的P2P流量识别模型,选取P2P流量的上/下行流量比,平均流速率、流持续时间、传输字节数、平均数据包长度等5个特征,对网络流量的P2P流量进行识别.实验结果表明,该方法能够有效地检测网络流量中的P2P流量,准确率达到96%.
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| 关 键 词： | 流量特征 支持向量机 对等网络 |
Research on a Method of P2P Traffic Detection Based on SVM |
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| JIANG Wei,WANG Chun-zhi,LUO Hong-fang,CHEN Hong-wei.Research on a Method of P2P Traffic Detection Based on SVM[J].Journal of Hubei University of Technology,2010,25(2):48-50. |
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| Authors: | JIANG Wei WANG Chun-zhi LUO Hong-fang CHEN Hong-wei |
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| Affiliation: | (School of Computer Science and Technology,Hubei University of Technology,430068) |
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| Abstract: | As a machine learning algorithm that has developed in recent years,SVM can be used to solve problems of highly nonlinear classification and regression.The paper proposes a P2P traffic identification model based on SVM.It identifies P2P traffic in network by choosing five characters of P2P traffic such as traffic ratio of up-going and down-going,average rate of traffic,traffic lasting hour,number of transmission bytes,and average height of data packet.Results of the experiment show the method can detect P2P traffic in network effectively with an accuracy of 96%. |
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| Keywords: | traffic character Support Vector Machine peer-to-peer |
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