Anatomy: Uncertain Data k-Anonymity Privacy Protection Algorithm

Xiangmin Ren; Boxuan Jia; Kechao Wang

doi:10.4028/www.scientific.net/AMM.433-435.1689

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 433-435Anatomy: Uncertain Data k-Anonymity Privacy...

Anatomy: Uncertain Data k-Anonymity Privacy Protection Algorithm

Abstract:

Uncertain data management has become an important research direction and a hot area of research. This paper proposes an UDAK-anonymity algorithm via anatomy for relational uncertain data. Uncertain data influence matrix based on background knowledge is built in order to describe the influence degree of sensitive attribute and Quasi-identifier (QI) attributes. We use generalization and BK(L,K)-clustering to present equivalent class, L makes sensitive attributes diversity in one equivalent class. Experimental results show that UDAK-anonymity algorithm are utility, effective and efficient, and can make anonymous uncertainty data effectively resist background knowledge attack and homogeneity attack.

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Periodical:

Applied Mechanics and Materials (Volumes 433-435)

Pages:

1689-1692

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.433-435.1689

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Online since:

October 2013

Authors:

Xiangmin Ren*, Boxuan Jia, Kechao Wang

Keywords:

Privacy Protection, UDAK-Anonymity, Uncertain Data

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