Parrot-Trained Adversarial Examples: Pushing the Practicality of Black-Box Audio Attacks against Speaker Recognition Models
Rui Duan
Network and Distributed System Security (NDSS) Symposium 2024 · Day 2 · ML Security
Speaker recognition systems, ubiquitous in smart devices and security applications, face a significant and evolving threat from **audio adversarial examples (AEs)**. While advancements in black-box attacks have been made, their real-world practicality has been hampered by the substantial information they demand from target models, often requiring extensive probing or knowledge of similarity scores. This research, presented by Rui Duan at the NDSS Symposium, tackles this critical challenge by proposing a novel mechanism designed to minimize the attacker's required knowledge, thereby significantly enhancing the practicality of black-box audio attacks.