Privacy Preservation by Disassociation

Provided by: University of Hohenheim
Topic: Data Management
Format: PDF
In this paper, the authors focus on protection against identity disclosure in the publication of sparse multidimensional data. Existing multi-dimensional anonymization techniques; protect the privacy of users either by altering the set of quasi-identifiers of the original data (e.g., by generalization or suppression) or by adding noise (e.g., using differential privacy) and/or assume a clear distinction between sensitive and non-sensitive information and sever the possible linkage. In many real world applications the above techniques are not applicable. For instance, consider web search query logs.

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