This work introduces an efficient algorithm to
develop a privacy-preserving (PP) voice verification based on
iVector and linear discriminant analysis techniques. This research
considers a scenario in which users enrol their voice biometric
to access different services (i.e., banking). Once enrolment is
completed, users can verify themselves using their voice-print
instead of alphanumeric passwords. Since a voice-print is unique
for everyone, storing it with a third-party server raises several
privacy concerns. To address this challenge, this work proposes
a novel technique based on randomisation to carry out voice authentication,
which allows the user to enrol and verify their voice
in the randomised domain. To achieve this, the iVector based
voice verification technique has been redesigned to work on the
randomised domain. The proposed algorithm is validated using
a well known speech dataset. The proposed algorithm neither
compromises the authentication accuracy nor adds additional
complexity due to the randomisation operations
