6 papers
SSTMark: Robust Training-Free Semantic-Level Speech Watermarking
Kuan-Lin Chu, Jun-Cheng Chen, Chun-Shien Lu
As speech generation models become increasingly realistic and widely accessible, concerns about the misuse, attribution, and governance of synthetic speech continue to grow. Waterm…
Rethinking Forgery Attacks on Semantic Watermarks in Black-Box Settings: A Geometric Distortion Perspective
Cheng-Yi Lee, Yichi Zhang, Yuchen Yang +2
Recent studies have shown that semantic watermarks, which embed information into the initial noise of latent diffusion models (LDMs), are vulnerable to black-box forgery attacks. H…
BadVim: Unveiling Backdoor Threats in Visual State Space Model
Cheng-Yi Lee, Yu-Hsuan Chiang, Zhong-You Wu +2
Visual State Space Models (VSSM) have shown remarkable performance in various computer vision tasks. However, backdoor attacks pose significant security challenges, causing comprom…
Safety Alignment Depth in Large Language Models: A Markov Chain Perspective
Ching-Chia Kao, Chia-Mu Yu, Chun-Shien Lu +1
Large Language Models (LLMs) are increasingly adopted in high-stakes scenarios, yet their safety mechanisms often remain fragile. Simple jailbreak prompts or even benign fine-tunin…
The Great Contradiction Showdown: How Jailbreak and Stealth Wrestle in Vision-Language Models?
Ching-Chia Kao, Chia-Mu Yu, Chun-Shien Lu +1
Vision-Language Models (VLMs) have achieved remarkable performance on a variety of tasks, yet they remain vulnerable to jailbreak attacks that compromise safety and reliability. In…
Defending Against Repetitive Backdoor Attacks on Semi-supervised Learning through Lens of Rate-Distortion-Perception Trade-off
Cheng-Yi Lee, Ching-Chia Kao, Cheng-Han Yeh +3
Semi-supervised learning (SSL) has achieved remarkable performance with a small fraction of labeled data by leveraging vast amounts of unlabeled data from the Internet. However, th…