Introduction:
The term ’big data’ has become appearing these days. With the universality of social networks, Internet of things (Iots) and outsourced cloud computing, we have seen a great growth of data in larger volume. Big data offers a great value and has become a driving force in economic growth.
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Application services and data business record user behaviors to improve their business skills and to accomplish their purpose. Growing techniques like social network, e-health system etc. offer excellent utilities for better understanding. It is now obvious that when users use these applications a lot of data points are formed and collected in real time. Well it also means that sensitive data becomes breachable. Privacy related problems occurs during data communication mining processes and even when raw data are not present because these sensitive data mining techniques can reveal private information.
With the improvement of privacy awareness, every institute is trying to develop solution to accomplish the increasing requirements of privacy safety. The goal is to make privacy safe so that people can work easily without any privacy leakage. Most of the privacy technologies use privacy preservation on
smaller scale. The task is to develop most efficient privacy preserving big data analytics which can deal with any type of data. In the past, communities have proposed many solutions.
From some past years many research groups take the challenge and create approaches. And they still discuss and developing more findings and clarify and summarize the existing approaches and contributions to prevent the privacy.