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Received:December 24, 2013 Revised:February 20, 2014
Received:December 24, 2013 Revised:February 20, 2014
中文摘要: 近年来，对互联网用户在网络上的行为分析研究吸引了广泛的兴趣，分析的结果对网络运营商和普通用户都有重要的意义. 研究用户在网络上的访问行为的类型识别问题，分析了一个由22 万个网络数据包组成的数据集，从中提取统计特征，设计用户网络访问的类型识别算法，实验结果显示本文算法具有相当高的识别准确率.
Abstract:In recent years, the research on analyzing the users' network behavior has attracted much attention. In this paper, we study the problem of identifying users' network behavior categories. The research is based on a dataset that consists of 220 thousand network packets, with which we extract the statistical features needed for the identifications. We propose the identifying algorithm, and we also apply the algorithm to make categories identification on the network dataset. The results show the presented work can achieve very high accuracy.
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基金项目:国家高技术研究发展计划（863）（2012AA12A203）
引用文本：
陈康,黄晓宇,陶彩霞,关迎晖,李磊,王爱宝.基于流量特征的用户互联网访问类型识别.计算机系统应用,2014,23(9):177-181
CHEN Kang,HUANG Xiao-Yu,TAO Cai-Xia,GUAN Ying-Hui,LI Lei,WANG Ai-Bao.Traffic Features Based Categories Identification on Users’ Network Be.COMPUTER SYSTEMS APPLICATIONS,2014,23(9):177-181
陈康,黄晓宇,陶彩霞,关迎晖,李磊,王爱宝.基于流量特征的用户互联网访问类型识别.计算机系统应用,2014,23(9):177-181
CHEN Kang,HUANG Xiao-Yu,TAO Cai-Xia,GUAN Ying-Hui,LI Lei,WANG Ai-Bao.Traffic Features Based Categories Identification on Users’ Network Be.COMPUTER SYSTEMS APPLICATIONS,2014,23(9):177-181
