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    ASIA unversity > 資訊學院 > 資訊工程學系 > 期刊論文 >  Item 310904400/6442


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    题名: TFRP: An Efficient Microaggregation Algorithm for Statistical Disclosure Control
    作者: Chang, C. C.;Li, Y. C.;Huang, W. H.
    关键词: Microaggregation;Disclosure control;k-Anonymity;Database security
    日期: 2007-09
    上传时间: 2009-12-17 06:57:59 (UTC+0)
    出版者: Asia University
    摘要: Recently, the issue of statistic disclosure control (SDC) has attracted much attention. SDC is a very important part of data security dealing with the protection of databases. Microaggregation for SDC techniques is widely used to protect confidentiality in statistical databases released for public use. The basic problem of microaggregation is that similar records are clustered into groups, and each group contains at least k records to prevent disclosure of individual information, where k is a pre-defined security threshold. For a certain k, an optimal multivariable microaggregation has the lowest information loss. The minimum information loss is an NP-hard problem. Existing fixed-size techniques can obtain a low information loss with O(n2) or O(n3/k) time complexity. To improve the execution time and lower information loss, this study proposes the Two Fixed Reference Points (TFRP) method, a two-phase algorithm for microaggregation. In the first phase, TFRP employs the pre-computing and median-of-medians techniques to efficiently shorten its running time to O(n2/k). To decrease information loss in the second phase, TFRP generates variable-size groups by removing the lower homogenous groups. Experimental results reveal that the proposed method is significantly faster than the Diameter and the Centroid methods. Running on several test datasets, TFRP also significantly reduces information loss, particularly in sparse datasets with a large k.
    關聯: Journal of Systems and Software 80:1866-1878
    显示于类别:[資訊工程學系] 期刊論文

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