(untitled) (International Journal of Engineering and Computer Science, 2017)
Data mining has attracted a great deal of information in recent years, due to the wide availability of huge amount of data and the imminent need for such data into useful information and knowledge, which can be used for applications ranging from market analysis, fraud detection and customer retention, to production control and science exploration. The real privacy concerns are with unconstrained access of individual records, like credit card, banking applications, customer ID, which must access privacy sensitive information. Due to privacy infringement while performing the data mining operations this is often not possible to utilize large databases for scientific or financial research. To address this problem, several privacy-preserving data mining techniques are used. The aim of privacy preserving data mining (PPDM) is to extract relevant knowledge from large amounts of data while protecting at the same time sensitive information.