Paper Title
Information Security: Concept of Privacy and Security with Data Mining

Abstract
Privacy-preserving data mining (PPDM) is one of the newest trends in privacy and security research. It is driven by one of the major policy issues of the information era: the right to privacy. Data mining is the process of automatically discovering high-level data and trends in large amounts of data that would otherwise remain hidden. The data mining process assumes that all the data is easily accessible at a central location or through centralized access mechanisms such as federated databases and virtual warehouses. However, sometimes the data are distributed among various parties. Privacy in terms of legal and commercial concerns may prevent the parties from directly sharing some sensitive data. Sensitive data usually includes information regarding financial privacy, etc. Privacy advocates and data mining are frequently at odds with each other, and bringing the data together in one place for analysis is not possible due to the privacy laws or policies. We introduced issues with PPDM and discussed some problems concerning the privacy of data mining and methods that can be adopted to protect sensitive information. We briefly introduce the vertical Partitioning and horizontal Partitioning. Also, Causes and privacy measure to be taken for securing privacy of data. Keywords - Data Mining, Sensitive Information, Privacy-Preserving Data Mining, Anonymization, Vertical Partitioning And Horizontal Partitioning