Name
Abstract | ||
|---|---|---|
Sharing users' positional information is often required for high accuracy localization, which is a cornerstone for numerous wireless applications in commercial, military, and social sectors. This raises a concern of leaking positional information to adversaries during the localization process. This paper establishes a mathematical foundation for location secrecy. In particular, we determine the location secrecy metric (LSM) for a localization network in which an eavesdropper has a generic measurement capability. We obtain a simple and closed-form expression of the LSM for the case where the eavesdropper's measurement of a user's position is corrupted by a Gaussian noise. We further extend this result to a more general measurement model, and design location secrecy protection strategies based on the insights gained from our analysis. The performance of the proposed algorithms is verified through numerical simulation. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC) | Location secrecy, location privacy, localization, wireless networks |
Field | DocType | ISSN |
Information system,Wireless,Computer simulation,Computer science,Secrecy,Computer network,Gaussian noise | Conference | 1550-3607 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenhan Dai | 1 | 222 | 17.69 |
| Moe Z. Win | 2 | 2225 | 196.12 |