基于方差分析和支持向量机技术的P2P流量检测

计算机科学 ›› 2010, Vol. 37 ›› Issue (8): 88-91.

• 计算机网络与信息安全 • 上一篇下一篇

基于方差分析和支持向量机技术的P2P流量检测

吴敏,王汝传

(南京邮电大学计算机学院南京210003)

出版日期:2018-12-01 发布日期:2018-12-01
基金资助:
本文受国家自然科学基金(60973139, 60773041)，江苏省自然科学基金(BK2008451)，省级现代服务业发展专项资金，江苏高校科技创新计划项目(CX09B_153Z,CX08B-086Z)，南京邮电大学青蓝工程项目(NY206034, NY208011)和江苏省六大高峰人才项目(2008118)资助。

P2P Traffic Identification Using Variance Analysis and Support Vector Machine Algorithm

WU Min,WANG Ru-chuan

Online:2018-12-01 Published:2018-12-01

摘要/Abstract

摘要： P2P流量逐渐成为了互联网流量的重要组成部分，在对Internet起巨大推动作用的同时，也带来了因资源过度占用而引起的网络拥塞以及安全隐患等问题，妨碍了正常的网络业务的开展。首先介绍了各种P2P流量识别方法及其优缺点，然后提出一种基于方差分析的P2P流量特征选择方法和基于该方法的支持向量机技术在P2P流量准实时检测中的应用模型。实验结果及分析表明，该方法能较有效地检测P2P流量并具有更好的检测精度。

关键词: 对等网络，流量检测，方差分析，支持向量机

Abstract: P2P traffic has taken great portions in the Internet traffic. While having a significant impact on the Internet,it brings serious problems such as network congestion and traffic hindrance caused by the excessive occupation in the bandwidth. The paper firstly introduced methods in identifying P2P traffic and their characters, then put forwards a P2P traffic feature selection method by exploring analysis of variance. Meanwhile a model based on Support Vector Machine (SVM) algorithm was set up to fulfill the quasi-real-time identification of P2P traffic. Experimental results show that the method is efficiency for P2P traffic identification and has a more accurate precision.

Key words: P2P network, Traffic identification, Analysis of variance, Support vector machine

吴敏,王汝传. 基于方差分析和支持向量机技术的P2P流量检测[J]. 计算机科学, 2010, 37(8): 88-91. https://doi.org/

WU Min,WANG Ru-chuan. P2P Traffic Identification Using Variance Analysis and Support Vector Machine Algorithm[J]. Computer Science, 2010, 37(8): 88-91. https://doi.org/