Abstract
A challenging task in privacy protection for public data is to realize an algorithm that generalizes a table according to a user’s requirement. In this paper, we propose an anonymization scheme for generating a k-anonymous table, and show evaluation results using three different tables. Our scheme is based on full-domain generalization and the requirements are automatically incorporated into the generated table. The scheme calculates the scores of intermediate tables based on user-defined priorities for attributes and selects a table suitable for the user’s requirements. Thus, the generated table meets user’s requirements and is employed in the services provided by users without any modification or evaluation.
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Kiyomoto, S., Tanaka, T. (2011). A User-Oriented Anonymization Mechanism for Public Data. In: Garcia-Alfaro, J., Navarro-Arribas, G., Cavalli, A., Leneutre, J. (eds) Data Privacy Management and Autonomous Spontaneous Security. DPM SETOP 2010 2010. Lecture Notes in Computer Science, vol 6514. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19348-4_3
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DOI: https://doi.org/10.1007/978-3-642-19348-4_3
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