Practical Applications of Secure Computation for Disclosure Control

Microdata dissemination normally requires data reduction and modification methods be applied, and the degree to which these methods are applied depend on the control methods that will be required to access and use the data. An approach that is in some circumstances more suitable for accessing data for statistical purposes is secure computation, which involves computing analytic functions on encrypted data without the need to decrypt the underlying source data to run a statistical analysis. This approach also allows multiple sites to contribute data while providing strong privacy guarantees. This way the data can be pooled and contributors can compute analytic functions without either party knowing their inputs. We explain how secure computation can be applied in practical contexts, with some theoretical results and real healthcare examples.