Identity Disclosure Protection in Slicing for Privacy Preservation

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Provided by: International Journal of Soft Computing and Engineering (IJSCE)
Topic: Data Management
Format: PDF
In recent years privacy preservation micro data publishing has gained wide popularity. Two of the most widely used anonymization techniques are generalization and bucketization. Bucketization doesn't prevent membership disclosure and it doesn't apply for data that don't have a clear distinction between quasi-identifiers and sensitive attribute. On the other hand, generalization loses high amount of data. A combination of both i.e., slicing provides better data utility but still its prone to attacks. Slicing protects the data against membership and attribute disclosure but it doesn't provide any details about identity disclosure.
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