A survey on privacy preserving data mining approaches and techniques

Abstract

In recent years, the importance of the Internet in our personal as well as our professional lives cannot be overstated as can be observed from the immense increase of its users. It therefore comes as no surprise that a lot of businesses are being carried out over the internet. It brings along privacy threats to the data and information of an organization. Data mining is the processing of analyze larger data in order to discover patterns and analyze hidden data concurring to distinctive sights for categorize into convenient information which is collected and assembled in common areas and other information necessities to eventually cut costs and increase revenue. In fact, the data mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, there was been growing concern that use of this technology is violating individual privacy. This tool aims to find useful patterns from large amount of data using by mining algorithms and approaches. The analysis of privacy preserving data mining (PPDM) algorithms should consider the effects of these algorithms in mining the results as well as in preserving privacy. Therefore, the success of privacy preserving data mining algorithms is measured in term of its performances, data utility, level of uncertainty, data anonymization, data randomization and so on based on data mining techniques and approaches are presented in this paper to analyze.