Privacy Preservation, Data Mining

Computer Engineering

The growing popularity and development of data mining technologies bring serious threat to the security of individual's sensitive information. An emerging research topic in data mining, known as privacy preserving data mining (PPDM), has been extensively studied in recent years. The basic idea of PPDM is to modify the data in such a way so as to perform data mining algorithms effectively without compromising the security of sensitive information contained in the data. Current studies of PPDM mainly focus on how to reduce the privacy risk brought by data mining operations, while in fact, unwanted disclosure of sensitive information may also happen in the process of data collecting, data publishing, and information (i.e., the data mining results) delivering. The author is trying to reduce the privacy risk brought by data mining operations. Privacy among the data provided is maintained. That is by preventing the any data leak, data movement or any third party access to it. Also maintain the refresh rate for third party access and performed the data mining using the k-means clustering. The collected data is showed in graph format which shows the histogram of average improvement of structure.

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