Preserving Privacy for Sensitive Data Items by Utilizing Data Mining Techniques

The enhancement of data mining technologies leads to the threat for privacy of individual's private information. In recent years Privacy Preserving Data Mining (PPDM) topic in data mining research is studied extensively. The motive of PPDM is to maintain data secure by performing data mining algorithms effectively. Current investigations of PPDM basically approaches to the very proficient method to lessen the protection attacks brought by data mining operations, while actually, undesirable revelation of sensitive data may also happen during the time spent data collecting, data distributing, and data (i.e., the information mining results) conveying. In this paper, mainly concentrate about the privacy threatening issues that were detected with information mining extracted from a huge data repositories and research different methodologies that can ensure sensitive data. The knowledge derived from their local data repositories is insufficient to meet their projected outcomes. Hence there exists a need for sharing data for effective data mining and better analysis. While performing data analysis there exists a chance for intruder to know the individuals sensitive information.