Integrating Private Databases for Data Analysis

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.

• Type: Conference
• Year: 2005
• Where: ISI
• Authors: Ke Wang, Benjamin C. M. Fung, Guozhu Dong
• Keywords: Integrated Data, ISI 2005, K-anonymity Privacy Requirement, Privacy Requirement