  In the present paper, we investigate the fundamental trade-off of
identification, secrecy, storage, and privacy-leakage rates in biometric
identification systems for hidden or remote Gaussian sources. We introduce a
technique for deriving the capacity region of these rates by converting the
system to one where the data flow is in one-way direction. Also, we provide
numerical calculations of three different examples for the generated-secret
model. The numerical results imply that it seems hard to achieve both high
secrecy and small privacy-leakage rates simultaneously. In addition, as special
cases, the characterization coincides with several known results in previous
studies.
