AN EFFICIENT SECURE COMPUTATION FOR PRIVACY PRESERVING DATA MINING IN MULTI PARTY COMPUTATION (MPC) – A REVIEW

In privacy preserving data mining, the relevant information from massive databases is extracted while safeguarding the sensitive data simultaneously. Secure MPC is a cooperative computation problem which safeguards privacies between a set of distrustful entities or participants. The review paper presents a detailed review of an efficient secure computation mechanism for boosting the privacy and security of data mining procedure in Multi-Party Computation (MPC) approach. It provides an overview of privacy preserving, data mining and multi-party computation. The paper highlights the usefulness and significance of secure computation techniques for privacy preserving in MPC. The prime motive of this paper is to investigate the effectiveness of conventional and existing computation approaches for privacy preserving and the research issues pertaining in this field. The work also presents past studies on data mining, secure computation and privacy preserving methods employed, their usefulness and shortcomings. The paper further provides the prominent technical gaps prevailing in existing literature pertaining to privacy preserving. It thereby presents a clear idea to researchers for upgrading the privacy preserving schemes in order to strengthen the security and for supporting the future improvements required in subsequent applications