基于用户代理及互联网知识的应用识别

doi:10.13190/j.jbupt.2017.02.017

北京邮电大学学报 ›› 2017, Vol. 40 ›› Issue (2): 102-105.doi: 10.13190/j.jbupt.2017.02.017

基于用户代理及互联网知识的应用识别

桂小林, 刘军, 乔媛媛, 池沐聪, 雷振明

北京邮电大学网络体系构建与融合北京市重点实验室, 北京 100876

收稿日期:2016-01-29 出版日期:2017-04-28 发布日期:2017-04-26
作者简介:桂小林(1984-),男,博士生,E-mail:guixiaolinde@gmail.com;雷振明(1951-),男,教授,博士生导师.
基金资助:
高等学校学科创新引智计划（111计划）项目（B08004）；国家自然科学基金项目（61601414）

Identifying Apps Based on User-Agent and Web-Knowledge

GUI Xiao-lin, LIU Jun, QIAO Yuan-yuan, CHI Mu-cong, LEI Zhen-ming

Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2016-01-29 Online:2017-04-28 Published:2017-04-26

摘要/Abstract

摘要： 为了在网络端识别安装在移动设备中的应用名称，提出了一种新的应用识别方法.该方法能根据模糊或不完整的用户代理（UA）特征字符串识别应用名称.首先，从超文本传输协议请求报文中获得UA特征；然后，从互联网中获取该UA对应的特征文本；最后，对该特征文本进行分析进而识别应用名称.基于大规模网络端采集的网络流量数据进行实验，结果表明所提方法的识别效果优于其他已知方法.

关键词: 应用识别, 互联网知识, 用户代理, 超文本传输协议

Abstract: A new method was proposed to identify apps via analyzing network traffic.This method can identify apps according to incomplete and ambiguous features of user-agent. Firstly, the user-agents from hyper text transfer protocol headers was extracted; then, the related text feature was obtained from Internet by using the corresponding user-agent; finally, the apps by analyzing the obtained text features was identified. Experiments are conducted by using hyper text transfer protocol traffic traces collected from Gn interface. It is shown that the proposed techniques are superior to the known methods.

Key words: application identification, web-knowledge, user-agent, hyper text transfer protocol

中图分类号:

TN911.22

桂小林, 刘军, 乔媛媛, 池沐聪, 雷振明. 基于用户代理及互联网知识的应用识别[J]. 北京邮电大学学报, 2017, 40(2): 102-105.

GUI Xiao-lin, LIU Jun, QIAO Yuan-yuan, CHI Mu-cong, LEI Zhen-ming. Identifying Apps Based on User-Agent and Web-Knowledge[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(2): 102-105.

参考文献

[1] Fiadino P, Bar A, Casas P. HTTPTag:a flexible on-line HTTP classification system for operational 3G networks[C]//2013 IEEE Conference on Computer Communications Workshop. Turin:IEEE, 2013:71-72.
[2] Gember A, Anand A, Akella A. A comparative study of handheld and non-handheld traffic in campus Wi-Fi networks[C]//Passive and Active Measurement. Berlin:Springer, 2011:173-183.
[3] Li Wei, Moore A W, Canini M. Classifying HTTP traffic in the new age[C]//ACM SIGCOMM. Seattle:ACM, 2008:17-22.
[4] 林平, 余循宜, 刘芳, 等. 基于流统计特性的网络流量分类算法[J]. 北京邮电大学学报, 2008, 31(2):15-19. Lin Ping, Yu Xunyi, Liu Fang, et al. A network traffic classification algorithm based on flow statistical characteristics[J]. Journal of Beijing University of Posts and Telecommunications, 2008, 31(2):15-19.
[5] Liu Jun, Li Tingting, Chen Gang. Mining and modeling the dynamic patterns of service providers in cellular data network based on big data analysis[J]. China Communications, 2013, 10(12):25-36.
[6] Dai Shuaifu, Tongaonkar A, Wang Xiaoyin, et al. Networkprofiler:towards automatic fingerprinting of Android apps[C]//2013 IEEE Conference on Computer Communications. Turin:IEEE, 2013:809-817.
[7] Miskovic S, Lee G M, Liao Y, et al. AppPrint:automatic fingerprinting of mobile applications in network traffic[C]//Passive and Active Measurement. Berlin:Springer, 2015:57-69.
[8] Xu Qiang, Erman J, Gerber A, et al. Identifying diverse usage behaviors of smartphone apps[C]//Proceedings of the 2011 ACM SIGCOMM Conference on Internet Measurement Conference. Berlin:ACM, 2011:329-344.
[9] Gui Xiaolin, Liu Jun, Chi Mucong, et al. Fine-grained analysis of cellular smartphone usage characteristics based on massive network traffic[J]. The Journal of China Universities of Posts and Telecommunications, 2016, 23(3):70-75.
[10] Sun Jian. Ansj 1.4[EB/OL].[2014-10-10]. https://github.com/NLPchina/ansj_seg.

[1]	袁建国余林峰游薇庞宇. 一种优化错误模式集的极化码 SCL-Flip 译码算法[J]. 北京邮电大学学报, 2023, 46(4): 76-82.
[2]	田心记王坤. IRS辅助下行NOMA系统中最大化折中的方法[J]. 北京邮电大学学报, 0, (): 0-0.
[3]	黄龙杨张楠刘笑笑申滨. 异构蜂窝网络中基于雾节点协作贡献度的计算卸载算法[J]. 北京邮电大学学报, 2023, 46(2): 37-42.
[4]	张浩冯春燕杨佳汇郭彩丽周博文. 面向语义通信的3D骨骼点数据编码与压缩方法[J]. 北京邮电大学学报, 2022, 45(6): 62-69.
[5]	王则予张梦菲孙耀华彭木根. 星上透明转发非地面网络中的切换机制研究[J]. 北京邮电大学学报, 2022, 45(6): 105-112.
[6]	朱剑锋孙耀华彭木根. 低轨卫星通信系统的前导序列设计研究[J]. 北京邮电大学学报, 2022, 45(6): 78-84.
[7]	牛凯吴泊霖戴金晟王森袁弋非. 面向6G系统的极化编码调制[J]. 北京邮电大学学报, 2022, 45(6): 1-11.
[8]	张顺外夏子寒. 基于SWIPT的乘积Polar编码协作构造与分析[J]. 北京邮电大学学报, 2022, 45(5): 54-59.
[9]	赵海英解光鹏高子惠. 基于数学规则的龟背纹自动生成方法[J]. 北京邮电大学学报, 2022, 45(4): 119-125.
[10]	赵海英, 解光鹏, 高子惠. 基于数学规则的龟背纹自动生成方法[J]. 北京邮电大学学报, 2022, 45(4): 110-115.
[11]	郭世泽, 吕仁健, 何明枢, 张杰, 俞赛赛. 流谱理论及其在网络防御中的应用[J]. 北京邮电大学学报, 2022, 45(3): 19-25.
[12]	王惠琴, 杨丽荣, 彭清斌, 曹明华, 陈丹. 基于离散小波变换的O-OFDM-DIM[J]. 北京邮电大学学报, 2022, 45(3): 57-63.
[13]	刘小明, 齐涛, 甘露. 一种宽带反射型极化旋转器[J]. 北京邮电大学学报, 2021, 44(6): 20-25,32.
[14]	刘绍华, 李明豪, 李兆歆, 毛天露, 刘京. 一种联合采样的神经网络光场[J]. 北京邮电大学学报, 2021, 44(6): 109-115.
[15]	赵海英, 李焕洪, 侯小刚. 基于感知驱动的纹饰矢量图评价方法[J]. 北京邮电大学学报, 2021, 44(6): 53-58.

基于用户代理及互联网知识的应用识别

Identifying Apps Based on User-Agent and Web-Knowledge

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价