Name
Abstract | ||
|---|---|---|
•First substantial effort to anonymize data streams having varied definitions.•Imputation free anonymization for varied data streams.•Transitive merging criteria that consider data distribution of partition selection.•Flexible re-using strategy to provide better anonymization with less computation time. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.ins.2018.07.057 | Information Sciences |
Keywords | Field | DocType |
Internet of things,Data privacy,Data streams,Anonymization,Missing values | Data mining,Data stream mining,Data stream,Tuple,k-anonymity,Artificial intelligence,Imputation (statistics),Missing data,Anonymity,Information privacy,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
467 | 0020-0255 | 2 |
PageRank | References | Authors |
0.36 | 25 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ankhbayar Otgonbayar | 1 | 2 | 1.37 |
| Zeeshan Pervez | 2 | 127 | 20.10 |
| K. P. Dahal | 3 | 27 | 5.78 |
| Steve Eager | 4 | 2 | 0.36 |