Multidimensional Techniques for Privacy Preservation in Datasets

Provided by: International Journal on Computer Science and Technology (IJCST)
Topic: Big Data
Format: PDF
Applications in commercial domains possess large datasets on individuals. This data includes private and sensitive information e.g. patient diseases, bank account details, organization structural details, etc. When data mining techniques are applied on these applications the private and sensitive information of the subjects will be revealed. However, it is necessary to share the information in such a way that the identities of the individuals are not revealed. So it is necessary to anonymize the data. For this the quasi-attribute set (attribute set that can be linked with original dataset to re-identify individuals) has to identified and anonymized.

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