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Assessing the information loss

Most anonymization techniques consist of reducing the level of detail in the information provided, or in suppressing information. They therefore typically result in loss of information. The challenge for the statistician is to strike a balance between the conflicting objectives of reducing the disclosure risk and minimizing this loss.

Various methods are available to assess information loss. For categorical data, these methods include direct comparison, comparison of contingency tables, and entropy-based measures. For continuous data, methods include comparisons of mean square, mean absolute, and mean variation.

Information on these techniques is available from the following resources.