| Electrical & Electronic Engineering |
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| ε-inclusion: privacy preserving re-publication of dynamic datasets |
| Qiong WEI, Yan-sheng LU, Lei ZOU |
| School of Computer Science and Technology, Huazhong University of Science and Techndogy, Wuhan 430074, China |
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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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Received: 17 November 2007
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