NDLI: All your location are belong to us: breaking mobile social networks for automated user location tracking

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All your location are belong to us: breaking mobile social networks for automated user location tracking

Content Provider	ACM Digital Library
Author	Gao, Zhaoyu Chen, Si Ren, Kui Yu, Le Zhu, Haojin Hu, Shangqian Li, Muyuan
Abstract	Location-based social networks (LBSNs) feature friend discovery by location proximity that has attracted hundreds of millions of users world-wide. While leading LBSN providers claim the well-protection of their users' location privacy, for the first time we show through real world attacks that these claims do not hold. In our identified attacks, a malicious individual with the capability of no more than a regular LBSN user can easily break most LBSNs by manipulating location information fed to LBSN client apps and running them as location oracles. We further develop an automated user location tracking system and test it on leading LBSNs including Wechat, Skout, and Momo. We demonstrate its effectiveness and efficiency via a 3 week real-world experiment on 30 volunteers and show that we could geo-locate any target with high accuracy and readily recover his/her top 5 locations. Finally, we also develop a framework that explores a grid reference system and location classifications to mitigate the attacks. Our result serves as a critical security reminder of the current LBSNs pertaining to a vast number of users.
Starting Page	43
Ending Page	52
Page Count	10
File Format	PDF
ISBN	9781450326209
DOI	10.1145/2632951.2632953
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-08-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Mobile social network Location privacy
Content Type	Text
Resource Type	Article

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