A Theoretical Comparison of Data Masking Techniques for Numerical Microdata

نویسندگان

  • Krish Muralidhar
  • Rathindra Sarathy
چکیده

In this study, we perform a comprehensive theoretical evaluation of masking techniques for numerical microdata. The objective of this comparison is to establish the extent to which existing techniques can satisfy disclosure risk, data utility, ease of implementation, and ease of use requirements. This evaluation allows data providers to select from these techniques to account for the demands of the data subjects and data users.

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تاریخ انتشار 2008