activity
20242026
collaborators

6 papers

cs.CR2026

DUAP: Dual-task Universal Adversarial Perturbations Against Voice Control Systems

Suyang Sun, Weifei Jin, Yuxin Cao +2

Modern Voice Control Systems (VCS) rely on the collaboration of Automatic Speech Recognition (ASR) and Speaker Recognition (SR) for secure interaction. However, prior adversarial a…

cs.SD2025

ALMGuard: Safety Shortcuts and Where to Find Them as Guardrails for Audio-Language Models

Weifei Jin, Yuxin Cao, Junjie Su +5

Recent advances in Audio-Language Models (ALMs) have significantly improved multimodal understanding capabilities. However, the introduction of the audio modality also brings new a…

cs.CR2025

Mirage Fools the Ear, Mute Hides the Truth: Precise Targeted Adversarial Attacks on Polyphonic Sound Event Detection Systems

Junjie Su, Weifei Jin, Yuxin Cao +3

Sound Event Detection (SED) systems are increasingly deployed in safety-critical applications such as industrial monitoring and audio surveillance. However, their robustness agains…

cs.CR2025

Whispering Under the Eaves: Protecting User Privacy Against Commercial and LLM-powered Automatic Speech Recognition Systems

Weifei Jin, Yuxin Cao, Junjie Su +6

The widespread application of automatic speech recognition (ASR) supports large-scale voice surveillance, raising concerns about privacy among users. In this paper, we concentrate…

cs.SD2025

Boosting the Transferability of Audio Adversarial Examples with Acoustic Representation Optimization

Weifei Jin, Junjie Su, Hejia Wang +2

With the widespread application of automatic speech recognition (ASR) systems, their vulnerability to adversarial attacks has been extensively studied. However, most existing adver…

cs.SD2024

Towards Evaluating the Robustness of Automatic Speech Recognition Systems via Audio Style Transfer

Weifei Jin, Yuxin Cao, Junjie Su +5

In light of the widespread application of Automatic Speech Recognition (ASR) systems, their security concerns have received much more attention than ever before, primarily due to t…