Sensitivity-Independent Differential Privacy via Prior Knowledge Refinement

Provided by: Universitat Rostock
Topic: Data Management
Format: PDF
The authors propose a new mechanism to implement differential privacy. Unlike the usual mechanism based on adding a noise whose magnitude is proportional to the sensitivity of the query function; their proposal is based on the refinement of the user's prior knowledge about the response. Their mechanism is shown to have several advantages over noise addition: it does not require complex computations, and thus it can be easily automated; it lets the user exploit her prior knowledge about the response to achieve better data quality; and it is independent of the sensitivity of the query function (although this can be a disadvantage if the sensitivity is small).

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