Name
Abstract | ||
|---|---|---|
Mobile crowdsourcing is being increasingly used by industrial and research communities to build realistic datasets. By leveraging the capabilities of mobile devices, mobile crowdsourcing apps can be used to track participants’ activity and to collect insightful reports from the environment (e.g., air quality, network quality). However, most of existing crowdsourced datasets systematically tag data samples with metadata (e.g., time and location stamps), which may inevitably lead to user privacy leaks by discarding sensitive information in the wild. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.jpdc.2020.07.011 | Journal of Parallel and Distributed Computing |
Keywords | DocType | Volume |
Distributed applications,Location privacy,Mobile crowdsourcing,Location privacy protection mechanism | Journal | 147 |
ISSN | Citations | PageRank |
0743-7315 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lakhdar Meftah | 1 | 0 | 1.35 |
| Romain Rouvoy | 2 | 929 | 70.34 |
| Isabelle Chrisment | 3 | 225 | 25.75 |