Big Data Security through Privacy – Preserving Data Mining (PPDM): A Decentralization Approach
R. Josphineleela, S. Kaliappan, L. Natrayan, Ashish Garg
Abstract
The increasing familiarity and improvements in data mining technologies bring serious security threats to the data of individuals. An emerging technology that provides better security and data security is PPDM: Privacy-Preserving Data Mining. The fundamental tenet of PPDM is to alter the data in such a manner that data mining techniques may be carried out successfully without affecting the privacy of sensitive data included in the data. The research article is focused on reducing the security and privacy risk that is created by data mining operations. During the process of data collection, Information processing, and publication of data there may be much security breached in the processing of the data in the data mining process. This paper focuses on the wide problems and is concerned with data mining, and finding a solution to ensure security and access through the data by diving the centralized data into various segments to ensure security by privacy-preserving methods. Through the process of finding various user interfaces related to data processing and issues related to the security of private information, this article will also show the vital role of PPDM in data mining and security.