Name
Abstract | ||
|---|---|---|
As location-based services become widely used in daily life, there is growing concern in preserving location privacy of users to avoid that attackers infer information about users by collecting and analyzing requests initiated by users. We argue that a good location privacy preservation scheme should have these properties. First, a user should never expose its precise location to any other entity. Second, a user should be able to specify its own requirement on the strength of privacy preservation, since a stricter preservation requirement may increase its overhead. Third, the scheme should be able to preserve as many as possible aspects of users' privacy under various attacks. With these desired properties in mind, we carefully design an encoding scheme of users' identifiers and a fully distributed architecture for our purpose and propose a privacy preservation scheme based on them. With the help of the encoding scheme and the distributed architecture, we develop a distributed negotiation algorithm to help users conduct negotiations among themselves to find their cloaked regions that satisfy their self-defined requirements without exposing their precise locations. The negotiations are completed without coordination from any central servers, and a random proxy is selected for each individual request, therefore the potential risks caused by any central server (location-based service servers or trusted-third-party servers) are mitigated as much as possible. Experiments show that our scheme can satisfy different strengths of privacy preservation required by each user even under the most severe scenarios. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ACCESS.2020.2978488 | IEEE ACCESS |
Keywords | DocType | Volume |
Privacy,Servers,Peer-to-peer computing,Resistance,Encoding,Computer architecture,Global Positioning System,k-anonymity,location-based service,location privacy,peer-to-peer | Journal | 8 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shengchao Liu | 1 | 2 | 1.05 |
| Jessie Hui Wang | 2 | 118 | 20.10 |
| Jilong Wang | 3 | 57 | 19.88 |
| Qianli Zhang | 4 | 24 | 5.41 |