Differential privacy

Differential privacy is a mathematically-rigorous definition of privacy. An algorithm uses a dataset to calculate its output. An algorithm is said to be differentially private if, based on its output, it is impossible to tell whether or not a particular individual was in the dataset.

In simpler terms, this property is fulfilled if the algorithm's behavior does not noticeably change when a single individual joins or leaves the dataset.

Use cases

Differential privacy is used in data collection on mobile devices. Operators can use this data for learning better models. One example is the keyboard data in Android. Another example is the usage data on iPhone