ABSTRACT
With the digitalization of the world, data is growing rapidly. A large amount of data is accumulated in all areas. Organizations store this data in a database as big data in a cluster. However, these clusters do not guarantee the security and confidentiality of the stored data. In recent years, data mining for privacy protection has become a popular research area for the protection of data stored as big data. There are many algorithms to keep data mining safe. This study focuses on knowledge mining by including security measures that must be applied at different stages of data mining. The different stages including data source, data miner and end-user are stored in the target database. Each step describes the risks involved in handling large amounts of data and the corresponding measures for data protection at each step.
