K-Anonymization Technique for Privacy Preserving in Big Data

Abstract

Big data has continues an rising in word of data analytics. Big data contain very large dataset and complex data structure. Traditional data model divided in the set of attributes like sensitive, quasi identifiers and non-sensitive attributes. Big data contain personal information that have privacy could be main. K-anonymization has been proposed as a mechanism for protecting privacy in big data. K-anonymization is a technique that prevents the above mentioned attacks by modifying the microdata which is released for business or research purposes. This is done by applying generalization and suppression techniques to the microdata. In this paper, k-anonymity is introduced and also some of the algorithms are studied which help in achieving k-anonymity.