TY - GEN
T1 - Defending against voice spoofing
T2 - 15th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2018
AU - Shang, Jiacheng
AU - Chen, Si
AU - Wu, Jie
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/6
Y1 - 2018/12/6
N2 - The recent proliferation of smartphones has been the primary driving factor behind the booming of voice-based mobile applications. However, the human voice is often exposed to the public in many different scenarios, and an adversary can easily steal a person’s voice and attack voice-based applications with the help of state-of-the-art voice synthesis/conversion soft-wares. In this paper, we propose a robust software-based voice liveness detection system for defending against voice spoofing attack. The proposed system is tailored for mobile platforms and can be easily integrated with existing mobile applications. We propose three approaches based on leveraging the vibration of human vocal cords, the motion of the human vocal system, and the functionality of vibration motor inside the smartphone. Experimental results show that our system can detect a live speaker with a mean accuracy of 94.38% and detect an attacker with a mean accuracy of 88.89% by combining three approaches we proposed.
AB - The recent proliferation of smartphones has been the primary driving factor behind the booming of voice-based mobile applications. However, the human voice is often exposed to the public in many different scenarios, and an adversary can easily steal a person’s voice and attack voice-based applications with the help of state-of-the-art voice synthesis/conversion soft-wares. In this paper, we propose a robust software-based voice liveness detection system for defending against voice spoofing attack. The proposed system is tailored for mobile platforms and can be easily integrated with existing mobile applications. We propose three approaches based on leveraging the vibration of human vocal cords, the motion of the human vocal system, and the functionality of vibration motor inside the smartphone. Experimental results show that our system can detect a live speaker with a mean accuracy of 94.38% and detect an attacker with a mean accuracy of 88.89% by combining three approaches we proposed.
KW - Liveness detection
KW - Voice authentication
UR - http://www.scopus.com/inward/record.url?scp=85060247255&partnerID=8YFLogxK
U2 - 10.1109/MASS.2018.00016
DO - 10.1109/MASS.2018.00016
M3 - Conference contribution
AN - SCOPUS:85060247255
T3 - Proceedings - 15th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2018
SP - 28
EP - 36
BT - Proceedings - 15th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 9 October 2018 through 12 October 2018
ER -