Adversarial attack and defense strategies of speaker recognition systems: A survey
Speaker recognition is a task that identifies the speaker from multiple audios. Recently,
advances in deep learning have considerably boosted the development of speech signal …
advances in deep learning have considerably boosted the development of speech signal …
“real attackers don't compute gradients”: bridging the gap between adversarial ml research and practice
Recent years have seen a proliferation of research on adversarial machine learning.
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …
Specpatch: Human-in-the-loop adversarial audio spectrogram patch attack on speech recognition
In this paper, we propose SpecPatch, a human-in-the loop adversarial audio attack on
automated speech recognition (ASR) systems. Existing audio adversarial attacker assumes …
automated speech recognition (ASR) systems. Existing audio adversarial attacker assumes …
Towards understanding and mitigating audio adversarial examples for speaker recognition
Speaker recognition systems (SRSs) have recently been shown to be vulnerable to
adversarial attacks, raising significant security concerns. In this work, we systematically …
adversarial attacks, raising significant security concerns. In this work, we systematically …
" Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences
D Olszewski, A Lu, C Stillman, K Warren… - Proceedings of the …, 2023 - dl.acm.org
Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …
seemingly contradictory results and expands the boundaries of known discoveries …
Query-efficient adversarial attack with low perturbation against end-to-end speech recognition systems
S Wang, Z Zhang, G Zhu, X Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the widespread use of automated speech recognition (ASR) systems in modern
consumer devices, attack against ASR systems have become an attractive topic in recent …
consumer devices, attack against ASR systems have become an attractive topic in recent …
{QFA2SR}:{Query-Free} Adversarial Transfer Attacks to Speaker Recognition Systems
Current adversarial attacks against speaker recognition systems (SRSs) require either white-
box access or heavy black-box queries to the target SRS, thus still falling behind practical …
box access or heavy black-box queries to the target SRS, thus still falling behind practical …
{V-Cloak}: Intelligibility-, Naturalness-& {Timbre-Preserving}{Real-Time} Voice Anonymization
Voice data generated on instant messaging or social media applications contains unique
user voiceprints that may be abused by malicious adversaries for identity inference or …
user voiceprints that may be abused by malicious adversaries for identity inference or …
{KENKU}: Towards Efficient and Stealthy Black-box Adversarial Attacks against {ASR} Systems
Prior researchers show that existing automatic speech recognition (ASR) systems are
vulnerable to adversarial examples. Most existing adversarial attacks against ASR systems …
vulnerable to adversarial examples. Most existing adversarial attacks against ASR systems …
RULER: discriminative and iterative adversarial training for deep neural network fairness
Deep Neural Networks (DNNs) are becoming an integral part of many real-world
applications, such as autonomous driving and financial management. While these models …
applications, such as autonomous driving and financial management. While these models …