A New Profile Based Privacy Measure for Data Publishing

Provided by: International Journal on Computer Science and Technology (IJCST)
Topic: Data Management
Format: PDF
The k-anonymity privacy requirement for publishing micro-data requires that each equivalence class (i.e., a set of records that are indistinguishable from each other with respect to certain \"Identifying\" attributes) contains at least k records. Recently, several authors have recognized that k-anonymity cannot prevent attribute disclosure. The notion of 'diversity has been proposed to address this; l-diversity requires that each equivalence class has at least 'well represented values for each sensitive attribute. In this paper, the authors follow that l-diversity has a number of limitations. In particular, it is neither necessary nor sufficient to prevent attribute disclosure.

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