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(l, e)-Diversity – A Privacy Preserving Model to Resist Semantic Similarity Attack

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First Author : Haiyuan Wang

Date of Publication : 2014-01-01

Journal : Journal of Computers

Affiliation of Author(s) : 数理与信息工程学院

Document Type : 期刊

Volume : Vol.9

Issue : No.1

Page Number : 59-64

ISSN : 1796-203X

Key Words : Data;privacy;l-diversity;(l;e)-diversity;anatomy;semantic;similarity;attack

Abstract : Existing sensitive attributes diversity models do not capture the semantic similarity between sensitive values, so they cannot resist semantic similarity attack. To address the problem, we present a method to measure semantic similarity of a categorical s

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