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iGPS: Privacy-Preserving Geo-Proximity Services in Location-based Social Networks (Jianliang Xu et al.)
A geo-proximity service in
location-based social networks alerts a mobile user when any of his/her friends
is in the geographical vicinity, so as to enrich social activities such as
collaborative working and information sharing. To realize such services,
existing systems collect location information from mobile users for proximity
computation, which raises serious privacy concerns. This project aims to
develop more sophisticated location update and query techniques that support
these geo-proximity services while preserving the location privacy of mobile
users.
Objectives:
- To identify the privacy requirements for mobile geo-proximity services such as distance-based proximity queries and nearest-friend queries
- To propose and develop location access and update techniques for proximity query and monitoring services to protect mutual privacy of mobile users
- To design and develop secure location access and query evaluation algorithms for nearest-friend queries with mutual privacy preservation requirements
- To develop a prototype system to demonstrate the security, feasibility and effectiveness of the proposed privacy-preserving solutions
Findings So Far:
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We have addressed the location privacy issue for the "nearby friend alert" service, a common and fundamental service in mobile geo-social networks. We have developed a new proximity detection scheme comprising a dynamic grid overlay and optimal grid placement based on the grid-and-hashing paradigm. The key advantage of this scheme over prior work is that users can dynamically trade accuracy for communication cost (or vice versa) in a quantitative manner, by adding (or removing) a number of grids. This advantage is particularly critical in mobile environments where bandwidth and battery conditions may change drastically.
Figure 1: Grid Overlay
Figure 2: Performance Results vs Grid Size
- We have proposed a notion of symmetric proximity detection, where two users
are considered to be in proximity only if they are located in each other’s
vicinity region. A new proximity detection algorithm has been developed without
leaking users’ location information to any third party. It divides the boundary
of a vicinity region into line segments, employs a shift-and-compare protocol
for each segment, and collectively decides whether there is any friend in the
vicinity region. This solution features 100% detection accuracy with low
communication and computation costs.
Figure 3: Shift-and-Compare Protocol
Publications:
- H. P. Li, H. Hu, and J. Xu. “Nearby Friend Alert: Location Anonymity in Mobile Geo-Social Networks.” IEEE Pervasive Computing (PC), in press, 2013. [DOI Bookmark, Press Coverage]
- X. Lin, H. Hu, H. Li, J. Xu, and B. Choi. “Private Proximity Detection and Monitoring with Vicinity Regions.” ACM SIGMOD Workshop MobiDE, June 2013.
Patent Application:
- “A System and Method for Providing Proximity Information” (with H. Hu). US Non-Provisional Patent Application No. 13/905,456, Filed in May 2013.
Grant Support:
This project is supported by the Research Grants Council (RGC), Hong Kong SAR, China (Project HKBU211512) and the Hong Kong Scholar Program (Grant XJ2011008).
For further information on this research topic, please contact Prof. Jianliang Xu.
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