计算机科学 ›› 2018, Vol. 45 ›› Issue (8): 7-12.doi: 10.11896/j.issn.1002-137X.2018.08.002

• 2017 中国多媒体大会 • 上一篇    下一篇

无线网络用户的Wi-Fi指纹匿名化研究

韩秀萍1, 王智1, 裴丹2   

  1. 清华大学深圳研究生院信息科学与技术学部 广东 深圳5180551
    清华大学计算机科学与技术系 北京1000842
  • 收稿日期:2017-10-24 出版日期:2018-08-29 发布日期:2018-08-29
  • 作者简介:韩秀萍(1993-),女,硕士,主要研究领域为用户行为分析、数据挖掘,E-mail:hxp15@mails.tsinghua.edu.cn; 王 智(1985-),男,博士,讲师,主要研究领域为多媒体内容分发、移动云计算、大范围多媒体系统,E-mail:wangzhi@sz.tsinghua.edu.cn(通信作者); 裴 丹(1973-),男,博士,副教授,主要研究领域为计算机网络,E-mail:peidan@tsinghua.edu.cn。

Study on Wi-Fi Fingerprint Anonymization for Users in Wireless Networks

HAN Xiu-ping1, WANG Zhi1, PEI Dan2   

  1. Department of Computer Science and Technology,Graduate School at Shenzhen,Tsinghua University,Shenzhen,Guangdong 518055,China1
    Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China2
  • Received:2017-10-24 Online:2018-08-29 Published:2018-08-29

摘要: 如今,上亿的Wi-Fi热点被广泛部署,用于给人们提供Wi-Fi连网服务。为了加快Wi-Fi连接的速度,移动设备会发送探测请求帧来发现附近的无线热点,并且保存曾经连接过的AP的SSID,即首选网络列表 (PNL)。已有研究表明,由探测请求帧发出的SSID构成的Wi-Fi指纹会泄露用户的隐私信息。基于对现实情况中Wi-Fi指纹所造成的隐私泄露程度的分析,提出了数据驱动的隐私保护方案。首先,针对4个城市中2700万用户连接400万Wi-Fi热点的行为进行了测量研究,并证明了在很多场景下Wi-Fi指纹都可以用来区分用户。基于对Wi-Fi指纹中SSID语义信息的研究,可以推断出这些用户的身份信息(如工作信息)。其次,提出了一种基于协同过滤的启发式方法,它通过给用户的PNL中添加伪SSID来模糊其信息,并使得附近的人彼此之间的PNL与Wi-Fi指纹都更加相似。最后,基于真实的Wi-Fi连接数据验证了上述策略的有效性,实验结果表明,修改PNL不仅能保护用户隐私,而且能保证快速的Wi-Fi连接。

关键词: 无线网络, 隐私泄露, 保护, 探测请求帧, 用户行为

Abstract: Billions of Wi-Fi assess points (APs) have been deployed to provide wireless connection to people with different kinds of mobile devices.Toaccelerate the speed of Wi-Fi connection,mobile devices will send probe requests to discover nearby Wi-Fi APs,and maintain previously connected network lists (PNLs) of APs.Previous studies show that the Wi-Fi fingerprints that consist of probed SSIDs individually will leak private information of users.This paper investigated the privacy caused by the Wi-Fi fingerprints in the wild,and provided a data-driven solution to protect privacy.First,measurement studies were carried out based on 27 million users associating with 4 million Wi-Fi APs in 4 cities,and it was revealed that Wi-Fi fingerprints can be used to identify users in a wide range of Wi-Fi scenarios.Based on semantic mining and analysis of SSIDs in Wi-Fi fingerprints,this paper further inferred demographic information of identified users (e.g.,people’s jobs),telling “who they are”.Second,this paper proposed a collaborative filtering (CF) based heuristic protection method,which can “blur” an user’s PNL by adding faked SSIDs,such that nearby users’ PNLs and Wi-Fi fingerprints are similar to each other.Finally,the effectiveness of the design was verified by using real-world Wi-Fi connection traces.The experiments show that the refined PNLs protect users’ privacy while still provide fast Wi-Fi reconnection.

Key words: Wireless network, Privacy leakage, Protection, Probe request frame, User behavior

中图分类号: 

  • TP393
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