6 papers
Query-Efficient Video Adversarial Attack with Stylized Logo on Service Computing
Duoxun Tang, Yuxin Cao, Xi Xiao +3
In service computing, video classification has become fundamental to many intelligent applications. While Deep Neural Networks (DNNs) have demonstrated excellent performance in rec…
Bones of Contention: Exploring Query-Efficient Attacks against Skeleton Recognition Systems
Yuxin Cao, Kai Ye, Derui Wang +4
Skeleton action recognition models have secured more attention than video-based ones in various applications due to privacy preservation and lower storage requirements. Skeleton da…
E2E-VGuard: Adversarial Prevention for Production LLM-based End-To-End Speech Synthesis
Zhisheng Zhang, Derui Wang, Yifan Mi +6
Recent advancements in speech synthesis technology have enriched our daily lives, with high-quality and human-like audio widely adopted across real-world applications. However, mal…
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…
SafeSpeech: Robust and Universal Voice Protection Against Malicious Speech Synthesis
Zhisheng Zhang, Derui Wang, Qianyi Yang +6
Speech synthesis technology has brought great convenience, while the widespread usage of realistic deepfake audio has triggered hazards. Malicious adversaries may unauthorizedly co…
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…