An Extensive Study on Statistical Data Anonymization Algorithms
Suman Madan, Puneet Goswami · 2018
Gigantic volume of detailed individual information is constantly gathered and divulging of these information is gainful for data mining application. Datais collected from thedata holders by various data publishers before beingthe release of data to the data beneficiary for the purpose of research analysis and mining. This released data may reveal the private and personal information of individuals. Thus arises the most important research issue of privacy in data publishing. Here, in this paper, we provided the analysis of the existing techniques for statistical data anonymization which are used for privacy preservation in published data along with the efficiency and effectiveness of each. This study will help the researchers to understand variety of different anonymization methods for microdata publishing, relationship between k-values, and anonymization degree and execution time.