|
Differential privacy is a statistical technique that aims to provide means to maximize the accuracy of queries from statistical databases while measuring the privacy impact on individuals whose information is in the database.
The goodness-of-fit test is a statistical hypothesis test to see how well sample data fit a distribution from a population. In other words, it tells you if your sample data represents the data you would expect to find in the actual population. Since those tests using sample data, to make it differentially private, privatized test procedures are required. By adjusting a goodness-of-fit test, the differentially private goodness-of-fit test can be used to test whether the samples are from a certain distribution. We want to find a test procedure to conduct a goodness-of-fit test while minimizing the privacy impact on individuals whose information is in the database or in the given sample data set when the population distribution is a continuous distribution.
|
