Computer Science ›› 2018, Vol. 45 ›› Issue (8): 7-12.doi: 10.11896/j.issn.1002-137X.2018.08.002

• ChinaMM 2017 • Previous Articles     Next Articles

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

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

CLC Number: 

  • TP393
[1]DAI Z,DINO A,MACAULAY S A.Attacking Automatic Wireless Network Selection[C]∥Proceedings of the Sixth Annual IEEE SMC Information Assurance Workshop.IEEE,2005:365-372.
[2]FREUDIGER J.How Talkative is Your Mobile Device?:An Experimental Study of Wi-Fi Probe Requests[C]∥Proceedings of the 8th ACM Conference on Security and Privacy in Wireless and Mobile Networks.ACM,2015.
[3]CHERNYSHEV M,VALLI C,HANNAY P.On 802.11 Access Point Locatability and Named Entity Recognition in Service Set Identifiers[J].IEEE Transactions on Information Forensics and Security,2016,11(3):584-593.
[4]FAN Y C,CHEN Y C,TUNG K C,et al.A Framework forEna-bling User Preference Profiling Through Wi-Fi Logs[J].IEEE Transactions on Knowledge and Data Engineering,2016,28(3):592-603.
[5]XU Q,ZHENG R,SAAD W,et al.Device Fingerprinting inWireless Networks:Challenges and Opportunities[J].IEEE Communications Surveys and Tutorials,2016,18 (1):94-104.
[6]CUNCHE M,KAAFAR M A,BORELI R.Linking Wireless Devices Using Information Contained in Wi-Fi Probe Requests[J].Pervasive and Mobile Computing,2014,11(4):56-69.
[7]BONNE B,QUAX P,LAMOTTE W.Raising Awareness onSmartphone Privacy Issues with SASQUATCH,and Solving Them with PrivacyPolice∥Proceedings of the 11th International Conference on Mobile and Ubiquitous Systems:Computing,Networking and Services.2014:379-381.
[8]LINDQVIST J,AURA T,DANEZIS G,et al.Privacy-preser-ving 802.11 Access-point Discovery[C]∥Proceedings of the Second ACM Conference on Wireless Network Security.ACM,2009:123-130.
[9]KIM Y S,TIAN T,NGUYEN L T,et al.Lapwin:Location-aided Probing for Protecting User Privacy in Wi-Fi Networks[C]∥Proceedings of IEEE Conference on Communications and Network Security.2014:427-435.
[10]PANG J,GREENSTEIN B,GUMMADI R,et al.802.11 User Fingerprinting[C]∥Proceedings of the 13th Annual ACM International Conference on Mobile Computing and Networking.ACM,2007:99-110.
[11]DESMOND L C C,YUAN C C,PHENG T C,et al.Identifying Unique Devices Through Wireless Fingerprinting[C]∥Procee-dings of the First ACM Conference on Wireless Network Security.ACM,2008:46-55.
[12]CHENG N,MOHAPATRA P,CUNCHE M,et al.InferringUser Relationship from Hidden Information in Wlans[C]∥Mi-litary Communications Conference.IEEE,2012:1-6.
[13]BARBERA M V,EPASTO A,MEI A,et al.Signals from The Crowd:Uncovering Social Relationships through Smartphone Probes[C]∥Proceedings of the 2013 Conference on Internet Measurement Conference.ACM,2013:265-276.
[14]LUZIO A D,MEI A,STEFA J.Mind Your Probes:De-anonymization of Large Crowds through Smartphone Wi-Fi Probe Requests[C]∥Proceedings of the 35th Annual IEEE International Conference on Computer Communications.IEEE,2016:1-9.
[15]SONG Y,YANG C,GU G.Who is Peeping at Your Passwords at Starbucks?-To Catch An Evil Twin Access Point[C]∥Proceedings of IEEE/IFIP International Conference on Dependable Systems and Networks.IEEE,2010:323-332.
[16]CALLEGATI F,CERRONI W,RAMILLI M.Man-in-the-Middle Attack to the Https Protocol[J].IEEE Security and Privacy,2009,7(1):78-81.
[17]SKINNER K,NOVAK J.Privacy and Your App[C]∥Apple Worldwide Dev.Conf.(WWDC).America,2015.
[18]Android 6.0 Changes[EB/OL]. marshmallow/android-6.0-changes.html.
[19]WANG W.Wireless Networking in Windows 10[C]∥Windows Hardware Engineering Community Conference (WinHEC).2015.
[20]VANHOEF M,MATTE C,CUNCHE M,et al.Why Mac Address Randomization is not Enough:An Analysis of Wi-Fi Network Discovery Mechanisms∥Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security.ACM,2016:413-424.
[21]VANHOEF M,MATTE C,CUNCHE M,et al.Why Mac Address Randomization is not Enough:An Analysis of Wi-Fi Network Discovery Mechanisms[C]∥Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security.ACM,2016:413-424.
[22]ZANG H,BOLOT J.Anonymization of Location Data does not Work:A Large-scale Measurement Study[C]∥Proceedings of the 17th Annual International Conference on Mobile Computing and Networking.ACM,2011:145-156.
[23]XU C,TENG J,JIA W.Enabling Faster and Smoother Handoffs in Ap-dense 802.11 Wireless Networks[J].Computer Communications,2010,33(15):1795-1803.
[24]TERVEEN L,HILL W.Beyond Recommender Systems:He-lping People Help Each Other[C]∥HCI in the New Millen-nium.2001:487-509.
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