Going In Style: Audio Backdoors Through Stylistic Transformations
Koffas, Stefanos, Pajola, Luca, Picek, Stjepan, Conti, Mauro
–arXiv.org Artificial Intelligence
This work explores stylistic triggers for backdoor attacks in the audio domain: dynamic transformations of malicious samples through guitar effects. We first formalize stylistic triggers - currently missing in the literature. Second, we explore how to develop stylistic triggers in the audio domain by proposing JingleBack. Our experiments confirm the effectiveness of the attack, achieving a 96% attack success rate. Our code is available in https://github.com/skoffas/going-in-style.
arXiv.org Artificial Intelligence
May-2-2023
- Country:
- Europe
- Italy (0.04)
- Netherlands > South Holland
- Delft (0.04)
- North America > United States
- California > Santa Clara County > Palo Alto (0.04)
- Europe
- Genre:
- Research Report > New Finding (0.94)
- Industry:
- Information Technology > Security & Privacy (1.00)
- Technology: