Practical Adversarial Attacks Against Speaker Recognition Systems

Author:

Li Zhuohang1,Shi Cong2,Xie Yi2,Liu Jian1,Yuan Bo2,Chen Yingying2

Affiliation:

1. The University of Tennessee, Knoxville, TN, USA

2. Rutgers University, New Brunswick, NJ, USA

Funder

Army Research Office

National Science Foundation

Air Force Research Laboratory

Publisher

ACM

Reference24 articles.

1. Detecting voice disguise from speech variability: Analysis of three glottal and vocal tract measures

2. Chase Bank. 2019. Security as unique as your voice. https://www.chase.com/personal/voice-biometrics Chase Bank. 2019. Security as unique as your voice. https://www.chase.com/personal/voice-biometrics

3. Audio Adversarial Examples: Targeted Attacks on Speech-to-Text

4. Speaker verification against synthetic speech

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1. An Initial Investigation of Neural Replay Simulator for Over-The-Air Adversarial Perturbations to Automatic Speaker Verification;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. Scalable Ensemble-Based Detection Method Against Adversarial Attacks For Speaker Verification;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Adversarial Transferability in Embedded Sensor Systems: An Activity Recognition Perspective;ACM Transactions on Embedded Computing Systems;2024-03-18

4. Signal Processing Interpretation for Adversarial Examples in Speaker Verification;2024 National Conference on Communications (NCC);2024-02-28

5. A Comprehensive Risk Analysis Method for Adversarial Attacks on Biometric Authentication Systems;IEEE Access;2024

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