June 22, 2021


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On Linear Time Decidability of Differential Privacy for Programs with Unbounded Inputs. (arXiv:2104.14519v1 [cs.CR])

We introduce an automata model for describing interesting classes of
differential privacy mechanisms/algorithms that include known mechanisms from
the literature. These automata can model algorithms whose inputs can be an
unbounded sequence of real-valued query answers. We consider the problem of
checking whether there exists a constant $d$ such that the algorithm described
by these automata are $depsilon$-differentially private for all positive
values of the privacy budget parameter $epsilon$. We show that this problem
can be decided in time linear in the automaton’s size by identifying a
necessary and sufficient condition on the underlying graph of the automaton.
This paper’s results are the first decidability results known for algorithms
with an unbounded number of query answers taking values from the set of reals.