K-anonymity

K-anonymity is the concept that each individual record in a dataset is indistinguishable from at least K other records based on certain attributes. This makes it challenging to identify each record individually, enhancing privacy protection.

Example

Considering attributes like gender, age, and location, if each record shares at least the same values with three other records, the data can be considered to have a 3-anonymity.

See Also

• L-diversity
• T-closeness