Differential privacy

Abstract

Differential privacy is a technology that allows sharing of information about a dataset while protecting individual privacy by adding noise to the results. It will have the following effect: if the arbitrary single substitution in the database is small enough, then the query result cannot be used to infer much about any single individual. In the cases of counting, summation, or average queries over a large, single table of data, Differential privacy is ready to be used effectively. One key drawback of differential privacy is that it often trades data accuracy for privacy. Differential privacy could be a great tool to help the government and large companies better comply with the demand for data privacy.