DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-3,Issue-4 ( Apr, 2016 ) | |||||||||
Paper Title |
R-Transform: Reversible Data Anonymity Base On Numeric Type Of Data In Outsourced Database | |||||||||
Author Name |
Iuon-Chang Lin, Yang-Te Lee | |||||||||
Affilition |
Department of Management Information Systems, National Chung Hsing University | |||||||||
Pages |
21-24 | |||||||||
Abstract |
—In recent years, a huge amount of data increased rapidly, we need more performance and bigger storage space to handle such data. Cloud service’s outsourced database is one of solution. But outsourced database has risk of privacy leak. So there have a scholar proposed a K-Anonymity to protect data’s privacy. K-Anonymity will let quasi-identifiers data attributes in the database be anonymized and preserve privacy. But K-Anonymity has a problem that data can’t be reversible. So we propose r-Transform to solve its problem. Our research uses on numeral data attribute. We use three parameters b1, b2and bitstreamto generate noise and change original data with this noise. It can interference attacker and reach the purpose of privacy-preserving. Index Terms—Data Anonymity, Reversible, Outsourced Database, privacy-preserving. | |||||||||
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