  This paper proposes a framework for group membership protocols preventing the
curious but honest server from reconstructing the enrolled biometric signatures
and inferring the identity of querying clients. This framework learns the
embedding parameters, group representations and assignments simultaneously.
Experiments show the trade-off between security/privacy and
verification/identification performances.
