期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：49
期号：2
出版社：Journal of Theoretical and Applied
摘要：Data mining services require accurate input data for their results to be meaningful, but privacy concerns may influence users to provide spurious information. The problem of privacy-preserving data mining has numerous applications in homeland security, medical database mining, and customer transaction analysis. The main feature of the most PPDM algorithms is that they usually modify the database through insertion of false information or through the blocking of data values in order to hide sensitive information. In this paper, we have incorporated the privacy preserving concept into the previously developed weighted utility mining approach. In this, we have presented an efficient algorithm for mining of privacy preserving high utility item sets by considering the sensitive item sets. The algorithm comprise of three major steps to attain the aim of our research includes, 1) Data sanitization, 2) Construction of sensitive utility FP-tree and, 3) Mining of sensitive utility item sets. The experimentation has carried out using real as well as the synthetic dataset and the performance of the proposed algorithm is evaluated with the aid of the evaluation metrics such as Miss cost and Database difference ratio.
关键词：Data Mining; Privacy Preserving Data; Utility Mining; Sanitized Data; Sensitive Item; Data Sanitization; Miss Cost; Database Difference Ratio.
