期刊名称：International Journal of Information Technology Convergence and Services (IJITCS)
印刷版ISSN：2231-1939
电子版ISSN：2231-153X
出版年度：2011
卷号：1
期号：2
出版社：AIRCC
摘要：Data mining researchers and policy makers have need of raw data collected from organizations and business companies for their analysis. Any transmission of data to third parties and the organizations outsourcing their wok should satisfy the privacy requirements in order to avoid the disclosure of sensitive information. In order to maintain privacy in databases, the confidential data should be protected in the form of modifying the sensitive data items. In statistical disclosure control, masking methods are used for modifying the confidential data. Most of the perturbative masking techniques existing in the literature are general purpose ones. In this work, a new perturbative masking technique called as modified data transitive technique (MDTT) is used for protecting the sensitive numerical attribute(s). The performance of the proposed technique (MDTT) is compared with the existing masking techniques additive noise, rounding and micro aggregation. The experimental result shows the MDTT technique has produced better results than existing techniques.
