期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2017
卷号：17
期号：12
页码：172-177
出版社：International Journal of Computer Science and Network Security
摘要：In today’s world, most organizations are facing data accumulation in massive amounts and storing them in large databases. Myriad of them, the particular healthcare industry has recognized the potential use of these data to make informed decisions. Data from the Electronic Health Records (EHRs) system are prone to privacy violations, especially when stored in healthcare medical servers. Privacy Preserving Data Publishing (PPDP) caters means to publish useful information while preserving data privacy by employing assorted anonymization methods. This paper provides a discussion on several anonymity techniques designed for preserving the privacy of microdata. This research aims to highlight three of the prominent anonymization techniques used in medical field, namely k-anonymity, l-diversity, and t-closeness. The benefits and limitations of these techniques are also reviewed.
关键词：PPDP data anonymization k-anonymity l-diversity t-closeness
