Inferential Privacy: From Impossibility to Database Privacy. (arXiv:2303.07782v1 [cs.CR])

We investigate the possibility of guaranteeing inferential privacy for
mechanisms that release useful information about some data containing sensitive
information, denoted by $X$. We describe a general model of utility and privacy
in which utility is achieved by disclosing the value of low-entropy features of
$X$, while privacy is maintained by keeping high-entropy features of $X$
secret. Adopting this model, we prove that meaningful inferential privacy
guarantees can be obtained, even though this is commonly considered to be
impossible by …

data database entropy features general high information low meaningful privacy prove release secret sensitive information utility value