JZUS - Journal of Zhejiang University SCIENCE

Journal of Zhejiang University SCIENCE A 2008 Vol.9 No.8 P.1124-1133

ε-inclusion: privacy preserving re-publication of dynamic datasets

Author(s): Qiong WEI, Yan-sheng LU, Lei ZOU
Affiliation(s): School of Computer Science and Technology, Huazhong University of Science and Techndogy, Wuhan 430074, China
Corresponding email(s): weijoan@gmail.com
Key Words: Privacy preservation, Re-publication, ε, -inclusion, Privacy principle

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Abstract: This paper presents a novel privacy principle, ε;-inclusion, for re-publishing sensitive dynamic datasets. ε;-inclusion releases all the quasi-identifier values directly and uses permutation-based method and substitution to anonymize the microdata. Combined with generalization-based methods, ε;-inclusion protects privacy and captures a large amount of correlation in the microdata. We develop an effective algorithm for computing anonymized tables that obey the ε;-inclusion privacy requirement. Extensive experiments confirm that our solution allows significantly more effective data analysis than generalization-based methods.

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