Cross-modal and Cross-medium Adversarial Attack for Audio

Author:

Zhang Liguo1ORCID,Tian Zilin1ORCID,Long Yunfei1ORCID,Li Sizhao1ORCID,Yin Guisheng1ORCID

Affiliation:

1. Harbin Engineering University, Harbin, China

Funder

Science and Technology on Sonar Laboratory

Publisher

ACM

Reference55 articles.

1. 1-Dimensional Polynomial Neural Networks for audio signal related problems

2. Alexei Baevski , Yuhao Zhou , Abdelrahman Mohamed , and Michael Auli . 2020. wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems , Vol. 33 ( 2020 ), 12449--12460. Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli. 2020. wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems, Vol. 33 (2020), 12449--12460.

3. Sören Becker , Marcel Ackermann , Sebastian Lapuschkin , Klaus-Robert Müller , and Wojciech Samek . 2018. Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals. CoRR , Vol. abs/ 1807 .03418 ( 2018 ). arxiv: 1807.03418 Sören Becker, Marcel Ackermann, Sebastian Lapuschkin, Klaus-Robert Müller, and Wojciech Samek. 2018. Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals. CoRR , Vol. abs/1807.03418 (2018). arxiv: 1807.03418

4. Wieland Brendel , Jonas Rauber , Matthias Bethge , and Decision-Based Adversarial . 2021. Decision-BasedAdversarialAttacks: ReliableAttacksAgainstBlack-Box Machine Learning Models. Advances in Reliably Evaluating and Improving Adversarial Robustness ( 2021 ), 77. Wieland Brendel, Jonas Rauber, Matthias Bethge, and Decision-Based Adversarial. 2021. Decision-BasedAdversarialAttacks: ReliableAttacksAgainstBlack-Box Machine Learning Models. Advances in Reliably Evaluating and Improving Adversarial Robustness (2021), 77.

5. Nicholas Carlini and David Wagner. 2017. Towards evaluating the robustness of neural networks. In ieee symposium on security and privacy (sp). Ieee 39--57. Nicholas Carlini and David Wagner. 2017. Towards evaluating the robustness of neural networks. In ieee symposium on security and privacy (sp). Ieee 39--57.

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