Abstract
Mobile geosocial networking services could be the killer app for next-generation mobile computing. However, the privacy issue - in particular, location privacy - has both users and government authors concerned. The authors address this issue for the 'nearby friend alert' service, common in mobile geosocial networks. They review representative works on privacy-preserving proximity detection and present a new quantitative solution. They adopt the grid-and-hashing paradigm and develop optimal grid overlay and multilevel grids to increase the detection accuracy while saving the wireless bandwidth. Based on these techniques, they devise the client-side location update scheme and the server-side update handling procedure for continuous proximity detection. Simulation results show that their approach is efficient and scalable under various system parameters and user moving speeds.
| Original language | English |
|---|---|
| Article number | 6392162 |
| Pages (from-to) | 62-70 |
| Number of pages | 9 |
| Journal | IEEE Pervasive Computing |
| Volume | 12 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Oct 2013 |
Scopus Subject Areas
- Software
- Computer Science Applications
- Computational Theory and Mathematics
User-Defined Keywords
- geosocial network
- location privacy
- location update
- mobile computing
- pervasive computing