Kui Ren - University at Buffalo
Students: Spring 2025, unless noted otherwise, sessions will be virtual on Zoom.
Breaking Mobile Social Networks for Automated User Location Tracking
Apr 01, 2015
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Abstract
Location-based social networks (LBSNs) feature location-based friend discovery services attracting hundreds of millions of active users world-wide. While leading LBSN providers claim the well-protection of their users' location privacy, in this talk we show for the first time through real world attacks that these claims do not hold after summarizing the existing practices from the industry. 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. I will further talk about the development of an automated user location tracking system based on the proposed attack and its test on leading LBSNs including Wechat, Skout, and Momo. Real-world experiments on 30 volunteers and the defense approaches will also be discussed. These findings serve as a critical security reminder of the current LBSNs pertaining to a vast number of users.About the Speaker

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