Graduate School and Research Center in Digital Sciences

On the vulnerability of automatic speaker recognition to spoofing attacks with artificial signals

Alegre, Federico; Vipperla, Ravichander; Evans, Nicholas; Fauve, Benoît

Research Report RR-12-266

Automatic speaker verification (ASV) systems are increasingly being used for biometric authentication even if their vulnerability to imposture or spoofing is now widely acknowledged. Recent work has proposed different spoofing approaches which can be used to test vulnerabilities. This paper introduces a new approach based on artificial, tone-like signals which provoke higher ASV scores than genuine client tests. Experimental results show degradations in the equal error rate from 8.5% to 77.3% and from 4.8% to 64.3% for standard Gaussian mixture model and factor analysis based ASV systems respectively. These findings demonstrate the importance of efforts to develop dedicated countermeasures, some of them trivial, to protect ASV systems from spoofing.

Document Bibtex

Title:On the vulnerability of automatic speaker recognition to spoofing attacks with artificial signals
Type:Report
Language:English
City:
Date:
Department:Digital Security
Eurecom ref:3683
Copyright: © EURECOM. Personal use of this material is permitted. The definitive version of this paper was published in Research Report RR-12-266 and is available at :
Bibtex: @techreport{EURECOM+3683, year = {2012}, title = {{O}n the vulnerability of automatic speaker recognition to spoofing attacks with artificial signals}, author = {{A}legre, {F}ederico and {V}ipperla, {R}avichander and {E}vans, {N}icholas and {F}auve, {B}eno{\^i}t}, number = {EURECOM+3683}, month = {03}, institution = {Eurecom}, url = {http://www.eurecom.fr/publication/3683},, }
See also: