期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2012
卷号：3
期号：4
页码：148-151
语种：English
出版社：Ayushmaan Technologies
摘要：Many organizations often need to publish their data for research and other purposes. The data contains individuals’ information that may be sensitive. So data anonymization must be provided. For maintaining individual privacy of people whose data is needed to be kept private, as one of many anonymization techniques, k-anonymity is introduced. It requires equivalence classes that contain at least k records. One of two basic problems of privacy in data publishing identity disclosure is prevented by k-anonymity as proved. But another problem attribute is not solved by k-anonymity. In attribute disclosure problem, the data generally contains multiple attribute, which are needed to be generalized and sometimes suppressed to provide anonymity. For this generalization/suppression techniques were introduced to prevent attribute disclosure in k-anonymity. But as observed keenly these techniques also contain several drawbacks. To avoid the problem of above techniques, Microaggregation for k-anonymity is introduced. A Multivariate microaggregation method is proposed here to prevent attribute disclosure effectively.
