T-Closeness Slicing: A New Privacy-Preserving Approach for Transactional Data Publishing

Volume: 30, Issue: 3, Pages: 438 - 453
Published: Aug 1, 2018
Abstract
Privacy-preserving data publishing has received much attention in recent years. Prior studies have developed various algorithms such as generalization, anatomy, and L-diversity slicing to protect individuals’ privacy when transactional data are published for public use. These existing algorithms, however, all have certain limitations. For instance, generalization protects identity privacy well but loses a considerable amount of information....
Paper Details
Title
T-Closeness Slicing: A New Privacy-Preserving Approach for Transactional Data Publishing
Published Date
Aug 1, 2018
Volume
30
Issue
3
Pages
438 - 453
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