  We study the problem of maximizing privacy of quantized sensor measurements
by adding random variables. In particular, we consider the setting where
information about the state of a process is obtained using noisy sensor
measurements. This information is quantized and sent to a remote station
through an unsecured communication network. It is desired to keep the state of
the process private; however, because the network is not secure, adversaries
might have access to sensor information, which could be used to estimate the
process state. To avoid an accurate state estimation, we add random numbers to
the quantized sensor measurements and send the sum to the remote station
instead. The distribution of these random variables is designed to minimize the
mutual information between the sum and the quantized sensor measurements for a
desired level of distortion -- how different the sum and the quantized sensor
measurements are allowed to be. Simulations are presented to illustrate our
results.
