  We consider the setting of publishing data without leaking sensitive
information. We do so in the framework of Robust Local Differential Privacy
(RLDP). This ensures privacy for all distributions of the data in an
uncertainty set. We formulate the problem of finding the optimal data release
protocol as a robust optimization problem. By deriving closed-form expressions
for the duals of the constraints involved we obtain a convex optimization
problem. We compare the performance of four possible optimization problems
depending on whether or not we require robustness in i) utility and ii)
privacy.
