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2007
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On Privacy-Preservation of Text and Sparse Binary Data with Sketches

10 years 1 months ago
On Privacy-Preservation of Text and Sparse Binary Data with Sketches
In recent years, privacy preserving data mining has become very important because of the proliferation of large amounts of data on the internet. Many data sets are inherently high dimensional, which are challenging to different privacy preservation algorithms. However, some domains of such data sets also have some special properties which make the use of sketch based techniques particularly useful. In this paper, we present a new method for privacy preserving data mining of text and binary data with the use of a sketch based approach. The special properties of such data sets which are exploited are that of sparsity; according to this property, only a small percentage of the attributes have non-zero values. We formalize an anonymity model for the sketch based approach, and utilize it in order to construct sketch based privacy preserving representations of the original data. This representation allows accurate computation of a number of important data mining primitives such as the dot ...
Charu C. Aggarwal, Philip S. Yu
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2007
Where SDM
Authors Charu C. Aggarwal, Philip S. Yu
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