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Slicing: A New Approach to Privacy Preserving Data Publishing

Slicing: A New Approach to Privacy Preserving Data Publishing,Computing Research Repository,Tiancheng Li,Ninghui Li,Jian Zhang,Ian Molloy

Slicing: A New Approach to Privacy Preserving Data Publishing   (Citations: 3)
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Several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving microdata publishing. Recent work has shown that general- ization loses considerable amount of information, especially for high-dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi- identifying attributes and sensitive attributes. In this paper, we present a novel technique called slicing, which partitions the data both horizontally and vertically. We show that slicing preserves better data utility than gen- eralization and can be used for membership disclosure pro- tection. Another important advantage of slicing is that it can handle high-dimensional data. We show how slicing can be used for attribute disclosure protection and develop an ef- ficient algorithm for computing the sliced data that obey the ℓ-diversity requirement. Our workload experiments confirm that slicing preserves better utility than generalization and is more effective than bucketization in workloads involving the sensitive attribute. Our experiments also demonstrate that slicing can be used to prevent membership disclosure.
Journal: Computing Research Repository - CORR , vol. abs/0909.2, 2009
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    • ...To minimize the privacy risks, prior methods in k-anonymity [17,16] and its variants [21,6,11], � -diversity [18,13,14,23] and t-closeness [9,10] emphasized on reducing identity disclosure and attribute disclosure [7]...
    • ...A few variants of k-anonymity also exist, e.g., Anatomy [21] which bucketizes sensitive values instead of QIDs, Micro-aggregation [6,15] and Slicing [11]...

    Yuan Fanget al. Privacy beyond Single Sensitive Attribute

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