Abstract: The boost in data storage capacity and computing power due to advancement in cloud computing and big data have extended the reach of information to the third party such as census data, medical data, and personal consumption data. However, privacy protection is one of the most concerned issues in big data and cloud. As big data and clouds hold user-specific information and therefore, we can't directly share an individual's data for analysis as this will lead to threats to user’s privacy. Hence, to preserve privacy during big data publishing and cloud computing we can use Anonymization techniques. To anonymize the data, the data privacy models such as k-anonymity, l-diversity, t-closeness are used. This survey paper first describes the privacy models used to anonymize the data and further share the concept of the different algorithms used to implement k-anonymity.
Keywords: Anonymization, K-anonymity, l-diversity, t-closeness., k-anonymity algorithm.
Title: K-Anonymity: Tool for preserving Privacy
Author: Shrinkhala Shinghai , Somesh Dewangan , Rahul Mishra
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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