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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Integrating Private Databases for Data Analysis
verfasst von : Ke Wang, Benjamin C. M. Fung, Guozhu Dong
Erschienen in: Intelligence and Security Informatics
Verlag: Springer Berlin Heidelberg
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In today’s globally networked society, there is a dual demand on both information sharing and information protection. A typical scenario is that two parties wish to integrate their private databases to achieve a common goal beneficial to both, provided that their privacy requirements are satisfied. In this paper, we consider the goal of building a classifier over the integrated data while satisfying the
k
-anonymity privacy requirement. The
k
-anonymity requirement states that domain values are generalized so that each value of some specified attributes identifies at least
k
records. The generalization process must not leak more specific information other than the final integrated data. We present a practical and efficient solution to this problem.