Minimal Knowledge PT-AE Attacks on Black-Box Speaker Recognition Models

Table of Links

Abstract and Intro

Background and Motivation

Parrot Training: Feasibility and Evaluation

PT-AE Generation: A Joint Transferability and Perception Perspective

Optimized Black-Box PT-AE Attacks

Experimental Evaluations

Related Work

Conclusion and References

Appendix

VIII. CONCLUSION

In this work, we investigated using the minimum knowledge of a target speaker’s speech to attack a black-box target speaker recognition model. We extensively evaluated the feasibility of using state-of-the-art VC methods to generate parrot speech samples to build a PT-surrogate model and the generation methods of PT-AEs. It is shown that PT-AEs can effectively transfer to a black-box target model and the proposed PT-AE attack has achieved higher ASRs and better perceptual quality than existing methods against both digital-line speaker recognition models and commercial smart devices in over-the-air scenarios.

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