Name
Title | ||
|---|---|---|
Tradeoff Between Location Quality and Privacy in Crowdsensing: An Optimization Perspective. |
Abstract | ||
|---|---|---|
Crowdsensing enables a wide range of data collection, where the data are usually tagged with private locations. Protecting users' location privacy has been a central issue. The study of various location perturbation techniques, e.g., k-anonymity, for location privacy has received widespread attention. Despite the huge promise and considerable attention, provable good algorithms considering the tra... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/JIOT.2020.2972555 | IEEE Internet of Things Journal |
Keywords | DocType | Volume |
Privacy,Crowdsensing,Degradation,Optimization,Perturbation methods,Sensors,Approximation algorithms | Journal | 7 |
Issue | ISSN | Citations |
4 | 2327-4662 | 2 |
PageRank | References | Authors |
0.36 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuhui Zhang | 1 | 27 | 8.93 |
| Ming Li | 2 | 5595 | 829.00 |
| Dejun Yang | 3 | 1685 | 93.08 |
| Jian Tang | 4 | 1095 | 74.34 |
| Guoliang Xue | 5 | 4438 | 279.38 |
| Jia Xu | 6 | 32 | 10.50 |