《计算机应用研究》|Application Research of Computers

互联网流量分类中流量特征研究

Survey on traffic features in Internet traffic classification

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作者 刘珍,王若愚,蔡先发,唐德玉
机构 1.广东药科大学 医药信息工程学院,广州 510006;2.华南理工大学 信息工程研究中心,广州 510006
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文章编号 1001-3695(2017)01-0008-07
DOI 10.3969/j.issn.1001-3695.2017.01.002
摘要 为了系统性分析互联网流量特征,根据统计对象或统计角度研究流量特征的归类法,展开评述了每类流量特征;针对流量特征的稳定性问题,分析报文抽样、网络环境和模糊化技术对流量特征的影响;从分类能力、稳定性、时效性和分类粒度等方面评述流量特征的优缺点,为流量特征应用提供指导性建议;最后总结了流量特征的未来研究方向。
关键词 互联网流量特征;互联网流量分类;网络测量;机器学习;连接图
基金项目 国家自然科学基金资助项目(61501128)
本文URL http://www.arocmag.com/article/01-2017-01-002.html
英文标题 Survey on traffic features in Internet traffic classification
作者英文名 Liu Zhen, Wang Ruoyu, Cai Xianfa, Tang Deyu
机构英文名 1.SchoolofMedicalInformationEngineering,GuangdongPharmaceuticalUniversity,Guangzhou510006,China;2.Information&NetworkEngineering&ResearchCenter,SouthChinaUniversityofTechnology,Guangzhou510006,China
英文摘要 In order to systematically analyze Internet traffic features, this paper researched the taxonomy of traffic features based on the objects used for building traffic features, and overviewed the related traffic features in each category.It further analyzed the stability of traffic features, the impact of packet sampling, network environment and obfuscating on traffic features.And then it compared the different kinds of traffic features from classification accuracy, stability, timeliness and granularity.Finally, this paper concluded future works about traffic features.
英文关键词 Internet traffic features; Internet traffic classification; network measurement; machine learning; connectivity graph
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收稿日期 2016/3/17
修回日期 2016/5/19
页码 8-14,41
中图分类号 TP393.06
文献标志码 A