What is 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.<ref>{{Cite web|url=https://privacytools.seas.harvard.edu/differential-privacy|title=Differential Privacy|website=privacytools.seas.harvard.edu|language=en|access-date=2019-05-11}}</ref> ==References== {{reflist}} [[Category:Computer security]] [[Category:Privacy]]