2023
DOI: 10.1109/access.2023.3234110
|View full text |Cite
|
Sign up to set email alerts
|

Exploring Diverse Feature Extractions for Adversarial Audio Detection

Abstract: Although deep learning models have exhibited excellent performance in various domains, recent studies have discovered that they are highly vulnerable to adversarial attacks. In the audio domain, malicious audio examples generated by adversarial attacks can cause significant performance degradation and system malfunctions, resulting in security and safety concerns. However, compared to recent developments in the audio domain, the properties of the adversarial audio examples and defenses against them still remai… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
references
References 40 publications
0
0
0
Order By: Relevance