Abstract
Present privacy preserving data publishing model only consider the tables with one sensitive attribute, so it isn’t match tables with multi-sensitive attributes. The approach based on multi-sensitive bucketization can protect the privacy of multi-sensitive attributes data publishing effectively, unfortunately, it is at a cost of hundreds of records being suppressed. This paper proposes an l-coverage cluster grouping model based on the same set of sensitive attributes to address the problem. On the premise of none suppressed record, a cluster algorithm is designed to implement the model. Extensive experiments illustrate that the new model can protect privacy of data with multi-sensitive attributes effectively and enforce the usability of data publishing.
Supported partially by the NFS of China under grants No.60773049.
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Jin, H., Liu, SC., Ju, SG. (2011). Privacy Preserving for Multiple Sensitive Attributes Based on l-Coverage. In: Wu, Y. (eds) High Performance Networking, Computing, and Communication Systems. ICHCC 2011. Communications in Computer and Information Science, vol 163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25002-6_45
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DOI: https://doi.org/10.1007/978-3-642-25002-6_45
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