Differential privacy with partial knowledge

Understand

Differential privacy offers formal quantitative guarantees for algorithms over datasets, but it assumes attackers that know and can influence all but one record in the database.

• This assumption often vastly overapproximates the attackers' actual strength, resulting in unnecessarily poor utility.
• Recent work has made significant steps towards privacy in the presence of partial background knowledge, which can model a realistic attacker's uncertainty.
• Prior work, however, has definitional problems for correlated data and does not precisely characterize the underlying attacker model.