Name
Abstract | ||
|---|---|---|
Keystroke data collected from smart devices includes various sensitive information about users. Collecting and analyzing such data raise serious privacy concerns. Google and Apple have recently applied local differential privacy (LDP) to address privacy issue on learning new words from users' keystroke data. However, these solutions require multiple LDP reports for a single word, which result in i... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TKDE.2018.2885749 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | Field | DocType |
Privacy,Servers,Dictionaries,Indexes,Frequency estimation | Data mining,Differential privacy,Computer science,Raw data,Keystroke logging,Information sensitivity | Journal |
Volume | Issue | ISSN |
32 | 3 | 1041-4347 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sungwook Kim | 1 | 25 | 3.50 |
| Hyejin Shin | 2 | 22 | 2.15 |
| Chung Hun Baek | 3 | 0 | 0.34 |
| Soo-Hyung Kim | 4 | 191 | 49.03 |
| Jun-Bum Shin | 5 | 37 | 2.72 |