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：2014
卷号：62
期号：1
出版社：Journal of Theoretical and Applied
摘要：Government Agencies and many other organizations often need to publish sensitive data � tables that contain unaggregated information about individuals. Sensitive data is a valuable source of information for the research and allocation of public funds, trend analysis and medical research. Publishing data about individuals without revealing sensitive information about them is a significant problem. A breach in the security of a sensitive data may expose the private information of an individual, or the interception of a private communication may compromise the security of a sensitive data. Private and Sensitive information is integral to many data repositories. The efficiency of privacy preserving data mining is crucial to many times�sensitive applications like medical data, voter registration data, census data, social network data and customer data. Where information dissemination is quick and easy, both individuals and custodians of data are getting increasingly cautious about privacy, security and ethical issues. In this paper privacy risks in publishing sensitive data and the design principles for developing counter measures are proposed. The main contributions of this study are four folds. First, domain knowledge about the Privacy and related issues is described. Secondly the definition of the utility of released data with reference to social network model is discussed. In the third fold, knowledge based attacks; vulnerabilities and risk analysis are given. Finally, the design considerations for developing countermeasures in privacy preserving sensitive data publishing are presented.
关键词：Data Mining; Data Anonymization; Privacy; Privacy Preservation; Data Publishing; Data Fusion; Data Security
