Preventing Information Lose and Membership Disclosure on Highdimensional Data

Abstract

The existing methods generalization and bucketization could not give a satisfactory result for privacy preserving on microdata. It results loss of information and some does not prevent the membership disclosure. In this paper, I present a new idea slicing, which partitions the data both horizontally and vertically. I justify that slicing preserves the data integrity and gives the member protection even it can handle high dimensional data. This can be used in protection of attribute disclosure and develop an algorithm to obey the ℓ-diversity requirement. Our experiments shows that slicing gives a better and effective utility better than the existing one.

Authors and Affiliations

A. Sridevi, S. Rama Sree

Keywords

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  • EP ID EP27754
  • DOI -
  • Views 285
  • Downloads 2

How To Cite

A. Sridevi, S. Rama Sree (2013). Preventing Information Lose and Membership Disclosure on Highdimensional Data. International Journal of Research in Computer and Communication Technology, 2(11), -. https://www.europub.co.uk/articles/-A-27754