Statements (18)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:privacy_model
|
| gptkbp:address |
background knowledge attack
|
| gptkbp:application |
data privacy
data anonymization |
| gptkbp:defines |
A privacy model that requires the distribution of a sensitive attribute in any equivalence class to be close to the distribution of the attribute in the overall table, with closeness measured by a threshold t.
|
| gptkbp:goal |
prevent attribute disclosure
|
| gptkbp:improves |
gptkb:l-diversity
|
| gptkbp:introduced |
gptkb:Suresh_Venkatasubramanian
gptkb:Ninghui_Li gptkb:Tiancheng_Li |
| gptkbp:introducedIn |
2007
|
| gptkbp:measures |
gptkb:Earth_Mover's_Distance
|
| gptkbp:publishedIn |
gptkb:IEEE_23rd_International_Conference_on_Data_Engineering_(ICDE_2007)
|
| gptkbp:relatedTo |
gptkb:k-anonymity
gptkb:l-diversity |
| gptkbp:bfsParent |
gptkb:Differential_Privacy
|
| gptkbp:bfsLayer |
5
|
| https://www.w3.org/2000/01/rdf-schema#label |
t-closeness
|