A Survey on Analytics for Preserving Privacy in Big Data

Background/Objectives: The age of big data is now coming. But the traditional data analytics may not be able to handle such large quantities of data. The question that arises now is how to develop a high performance platform to efficiently analyze big data and how to design an appropriate mining algorithm to find the useful things from big data. Findings: Limitations of big data analytics, applications of big data analytics in various fields are explained.To date; health care industry has not fully grasped the potential benefits to be gained from big data analytics. The open issues on computation, quality of end result, security, and privacy in platform/framework, data mining perspective are discussed to explain which open issues we may face. Methods: Methods for preserving privacy in big data analytics are also discussed.