A Comprehensive Survey on Privacy Preservation Algorithms in Data Mining

Abstract

The Evolutionary Enhancement in the technology Innovation, Fast Processing Procedures and Networking systems encouraged the Business organizations to gather and store large volume of data in the electronic form in nature. The Security and the privacy are the two major issues in the area of data mining. For solving such issues effectively privacy preserving data mining (PPDM) has emerged. The sensitive individual data, like individual health records, faces, and names are intentionally removed from the original data for the purpose of preserving privacy because such data are maliciously manipulated by the attacker. PPDM plays an important role in hiding such individual sensitive data. The main objective PPDM is to secure individual sensitive information. PPDM is not only for the prevention of individual information, take prevention methods towards leakage of any information. To solve the privacy issues in data mining there are various advanced techniques. These Methods are categorized by several types like cryptographic based Methods, Data Modification Based Methods, Query Auditing Methods and Data Transformation Based techniques etc. This paper gives Detailed Overview on privacy preserving techniques and further major enhancements in terms of Strong privacy Preservation methods as well as more preservation techniques should be implemented in future.