The dawn of a text-dependent society: deepfakes as a threat to
speech verification systems

D 2022

The dawn of a text-dependent society: deepfakes as a threat to speech verification systems

FIRC, Anton and Kamil MALINKA

Basic information

Original name

The dawn of a text-dependent society: deepfakes as a threat to speech verification systems

Authors

FIRC, Anton and Kamil MALINKA

Edition

SAC '22: Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing, p. 1646--1655, 2022

Publisher

Association for Computing Machinery

Other information

Type of outcome

Proceedings paper

Confidentiality degree

is not subject to a state or trade secret

Publication form

electronic version available online

DOI

https://doi.org/10.1145/3477314.3507013

Keywords in English

deepfakes, speech verification, voice biometrics, machine learning, cybersecurity

Abstract

In the original language

We are already aware that deepfakes pose threats to humankind. Nowadays, mostly as fake news or disinformation; however, there are still unexplored areas such as using deepfakes to spoof voice verification. We present a real-world use case for spoofing voice authentication in a customer care call center. Based on this scenario, we evaluate the feasibility of attacking such a system and create an attacker profile. For this purpose, we examine three available speech synthesis tools and discuss their usability. We use these tools and acquired knowledge to generate a dataset including deepfake speech and assess the resilience of voice biometrics systems against deepfakes. We prove that voice biometrics systems are indeed vulnerable to deepfake powered attacks. The most significant outcome is the proposal of text-dependent verification as a novel countermeasure for presented attacks. Text-dependent verification provides higher security than text-independent verification and can be used today as the simplest protection method against deepfakes.

Cite

FIRC, Anton and Kamil MALINKA. The dawn of a text-dependent society: deepfakes as a threat to speech verification systems. Online. In SAC '22: Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing. Association for Computing Machinery, 2022, p. 1646--1655. Available from: https://doi.org/10.1145/3477314.3507013.

@inproceedings{2213202,
   author = {Firc, Anton and Malinka, Kamil},
   booktitle = {SAC '22: Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing},
   doi = {https://doi.org/10.1145/3477314.3507013},
   keywords = {deepfakes, speech verification, voice biometrics, machine learning, cybersecurity},
   howpublished = {elektronická verze "online"},
   pages = {1646--1655},
   publisher = {Association for Computing Machinery},
   title = {The dawn of a text-dependent society: deepfakes as a threat to speech verification systems},
   year = {2022}
}

TY  - CONF
ID  - 2213202
AU  - Firc, Anton - Malinka, Kamil
PY  - 2022
TI  - The dawn of a text-dependent society: deepfakes as a threat to speech verification systems
PB  - Association for Computing Machinery
KW  - deepfakes, speech verification, voice biometrics, machine learning, cybersecurity
N2  - We are already aware that deepfakes pose threats to humankind. Nowadays, mostly as fake news or disinformation; however, there are still unexplored areas such as using deepfakes to spoof voice verification. We present a real-world use case for spoofing voice authentication in a customer care call center. Based on this scenario, we evaluate the feasibility of attacking such a system and create an attacker profile. For this purpose, we examine three available speech synthesis tools and discuss their usability. We use these tools and acquired knowledge to generate a dataset including deepfake speech and assess the resilience of voice biometrics systems against deepfakes. We prove that voice biometrics systems are indeed vulnerable to deepfake powered attacks. The most significant outcome is the proposal of text-dependent verification as a novel countermeasure for presented attacks. Text-dependent verification provides higher security than text-independent verification and can be used today as the simplest protection method against deepfakes.
ER  -

FIRC, Anton and Kamil MALINKA. The dawn of a text-dependent society: deepfakes as a threat to speech verification systems. Online. In \textit{SAC '22: Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing}. Association for Computing Machinery, 2022, p.~1646--1655. Available from: https://doi.org/10.1145/3477314.3507013.

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