Audio adversarial attack: HIS attack

Jian Ma; Da Luo

doi:10.1117/12.2640809

3 October 2022 Audio adversarial attack: HIS attack

Jian Ma, Da Luo

Proceedings Volume 12290, International Conference on Computer Network Security and Software Engineering (CNSSE 2022); 1229003 (2022) https://doi.org/10.1117/12.2640809
Event: International Conference on Computer Network Security and Software Engineering (CNSSE 2022), 2022, Zhuhai, China

Abstract

The adversarial example is an input carefully designed by the attacker to tamper with the output of the neural network model. The emergence of audio adversarial example is to tamper with the end-to-end automatic speech recognition (ASR) system results. Due to the high difficulty of tampering with the ASR recognition results, the noise produced by today’s audio adversarial example generation methods is still easy to be noticed by humans and machines. In this paper, we propose an audio adversarial example generation method that makes audio adversarial example difficult to be perceived based on time-domain restriction. This method hides the adversarial perturbation noise in the speech part of audio by limiting the adversarial perturbation noise in the time domain. Our proposed method is more difficult to be detected by detection methods of audio adversarial example with equal attack performance compared to existing methods. We call the proposed method the HIS (hide in speech) attack.

Citation Download Citation

Jian Ma and Da Luo "Audio adversarial attack: HIS attack", Proc. SPIE 12290, International Conference on Computer Network Security and Software Engineering (CNSSE 2022), 1229003 (3 October 2022); https://doi.org/10.1117/12.2640809

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