Anatomy: Uncertain Data k-Anonymity Privacy Protection Algorithm
2013 ◽
Vol 433-435
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pp. 1689-1692
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Keyword(s):
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.
2011 ◽
Vol 335-336
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pp. 419-422
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2014 ◽
Vol 596
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pp. 222-225
2011 ◽
Vol 55-57
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pp. 929-932
2012 ◽
Vol 157-158
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pp. 349-352
2011 ◽
Vol 284-286
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pp. 585-588
2010 ◽
Vol 171-172
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pp. 358-363
2014 ◽
Vol 1010-1012
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pp. 1618-1621
Keyword(s):
2011 ◽
Vol 109
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pp. 603-607
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