文章基本信息

标题：Microdata Protection Method Through Microaggregation: A Systematic Approach
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作者：Kabir, Md Enamul ; Wang, Hua
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2012
卷号：7
期号：11
页码：2415-2423
DOI：10.4304/jsw.7.11.2415-2423
语种：English
出版社：Academy Publisher
摘要：Microdata protection in statistical databases has recently become a major societal concern and has been intensively studied in recent years. Statistical Disclosure Control (SDC) is often applied to statistical databases before they are released for public use. Microaggregation for SDC is a family of methods to protect microdata from individual identification. SDC seeks to protect microdata in such a way that can be published and mined without providing any private information that can be linked to specific individuals. Microaggregation works by partitioning the microdata into groups of at least k records and then replacing the records in each group with the centroid of the group. This paper presents a clustering-based microaggregation method to minimize the information loss. The proposed technique adopts to group similar records together in a systematic way and then anonymized with the centroid of each group individually. The structure of systematic clustering problem is defined and investigated and an algorithm of the proposed problem is developed. Experimental results show that our method attains a reasonable dominance with respect to both information loss and execution time than the most popular heuristic algorithm called Maximum Distance to Average Vector (MDAV).
关键词：Privacy;Microaggregation;Microdata protection;k-anonymity;Disclosure contro