P2P流量识别技术综述

计算机科学 ›› 2011, Vol. 38 ›› Issue (10): 6-12.

P2P流量识别技术综述

刘三民,孙知信

(南京航空航天大学信息科学与技术学院南京210016);(南京邮电大学计算机技术研究所南京210003);(南京大学计算机软件新技术国家重点实验室南京210093);(安徽工程大学计算机与信息学院芜湖241000)

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受国家自然科学基金(60973140),江苏省自然基金(BK2009425),江苏省高校自然科学基础研究项目(08KJB520005),江苏省六大人才高峰项目资助.

Survey of the P2P Trffic Identification Techniques

LIU San-min, SUN Zhi-xin

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 分析了P2P流量识别的重要性，通过系统归纳现有文献，按流量识别机制将现有识别方案分为基于端口识别法、应用层特征识别法、传输层特征识别法和机器学习方法4大类。并详细地剖析每类识别方法的原理、涉及的关键问题以及解决这些问题的具体方法和国内外的研究进展，讨论各自存在的优缺点。在此基础之上对未来可能出现的研究趋势做了展望。

关键词: 流量识别，机器学习，决策树，支持向量机

Abstract: This paper analysed the importance of P2P traffic identification. 13y summarizing literature, the existing method was divided into four kinds of traffic identification according to the mechanism of identification; port based classificanon, application-layer signatures, transport layer feature and machine learning. This study analysed in detail the principle of traffic identification and the critical problem and explored the recent research at home and abroad, measures to solve the problem and advantages and disadvantages. Following it, this paper made prospect for the future research trends.

Key words: Traffic identification,Machine learning,Decision tree,Support vector machine

刘三民,孙知信. P2P流量识别技术综述[J]. 计算机科学, 2011, 38(10): 6-12. https://doi.org/

LIU San-min, SUN Zhi-xin. Survey of the P2P Trffic Identification Techniques[J]. Computer Science, 2011, 38(10): 6-12. https://doi.org/

参考文献

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed