[1]商正仪,梁羽燕,薛建宇,等.基于移动终端的无线局域网用户行为研究[J].计算机技术与发展,2018,28(03):132-136.[doi:10.3969/ j. issn.1673-629X.2018.03.028]
　SHANG Zheng-yi,LIANG Yu-yan,XUE Jian-yu,et al.Research on User Behavior of WLAN Based on Mobile Terminals[J].,2018,28(03):132-136.[doi:10.3969/ j. issn.1673-629X.2018.03.028]
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基于移动终端的无线局域网用户行为研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年03期
页码:
132-136
栏目:
安全与防范
出版日期:
2018-03-10

文章信息/Info

Title:
Research on User Behavior of WLAN Based on Mobile Terminals
文章编号:
1673-629X(2018)03-0132-05
作者:
商正仪; 梁羽燕; 薛建宇; 陈 伟
南京邮电大学 计算机学院,江苏 南京 210046
Author(s):
SHANG Zheng-yi; LIANG Yu-yan; XUE Jian-yu; CHEN Wei
School of Computer,Nanjing University of Posts and Telecommunications,Nanjing 210046,China
关键词:
无线局域网; 用户行为分析; 聚类; 隐私分析; 机器学习
Keywords:
WLAN; user behavior analysis; cluster; privacy analysis; machine learning
分类号:
TP393.1
DOI:
10.3969/ j. issn.1673-629X.2018.03.028
文献标志码:
A
摘要:
由于无线空间传播信道所独具的开放性以及特殊辐射性,产生了许多隐私泄露的隐患。 实验在公共环境下对无线局域网通信数据进行了还原,基于当前多类市场主流终端应用充分挖掘了无线网用户行为。 在对用户及其行为建模之后,采用基于加权相似度的非监督聚类算法,进一步研究用户的社会性特征与潜在兴趣趋向。 目的是明确用户的真正需求,增加用户之间的直接关联,便于设计更加贴近用户的协议与服务,优化改进无线网络机制。 实验结果表明,该方法能够有效分析用户行为,聚类用户群体,有助于改善无线网用户使用体验,防范用户隐私泄露以及定制个性化网络服务。
Abstract:
There are many hidden dangers of privacy leakage due to the openness and special radiation of wireless communication channel. The communication data from WLAN is restored in the public environment,and the wireless network users behavior is fully exploited based on the mainstream terminal application in current market. After modeling the users and their behavior,we adopt the non-supervised clustering algorithm based on weighed similarity for further study of the social characteristics and potential interest trend of users. We aim
to clarify the user’s real demand and increase the direct relation between users,in order to design the agreement and service which are more close to users,and optimize the wireless network mechanism. Experiment shows that this method can effectively analyze user’s behavior and cluster user groups,which is help improve the user experience,prevent user’s privacy disclosure and customize personalized web service.

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更新日期/Last Update: 2018-04-26