Data Privacy Preservation and Security Approaches for Sensitive Data in Big Data

Data mining is a technique that explores the necessary data extracted from large sets. Privacy protection of about hiding sensitive information or identity breach security without losing usability. Sensitive contains confidential individuals, businesses, and governments who must not agree upon before sharing publishing his privacy data. Conserving has become critical research area. Various evaluation metrics such as performance in terms time efficiency, utility, degree complexity resistance to techniques are used estimate preservation techniques. Social media smart phones produce tons every minute. To decision making, voluminous produced different sources can be processed analyzed. But analytics vulnerable breaches privacy. One frameworks recommendation systems commonly by e-commerce sites Amazon, Flip Kart recommend items customers based on their purchasing habits lead characterized. This paper presents various conservation, anonymization, randomization, generalization, permutation, etc. which existing researchers use. We also analyze gap between processes methods illustrate how overcome issues with new innovative methods. Finally, our describes outcome summary entire literature.