6 papers
ID-Eraser: Proactive Defense Against Face Swapping via Identity Perturbation
Junyan Luo, Peipeng Yu, Jianwei Fei +4
Deepfake technologies have rapidly advanced with modern generative AI, and face swapping in particular poses serious threats to privacy and digital security. Existing proactive def…
Cheating Stereo Matching in Full-scale: Physical Adversarial Attack against Binocular Depth Estimation in Autonomous Driving
Kangqiao Zhao, Shuo Huai, Xurui Song +1
Though deep neural models adopted to realize the perception of autonomous driving have proven vulnerable to adversarial examples, known attacks often leverage 2D patches and target…
TrojanPraise: Jailbreak LLMs via Benign Fine-Tuning
Zhixin Xie, Xurui Song, Jun Luo
The demand of customized large language models (LLMs) has led to commercial LLMs offering black-box fine-tuning APIs, yet this convenience introduces a critical security loophole:…
Attack via Overfitting: 10-shot Benign Fine-tuning to Jailbreak LLMs
Zhixin Xie, Xurui Song, Jun Luo
Despite substantial efforts in safety alignment, recent research indicates that Large Language Models (LLMs) remain highly susceptible to jailbreak attacks. Among these attacks, fi…
Where to Start Alignment? Diffusion Large Language Model May Demand a Distinct Position
Zhixin Xie, Xurui Song, Jun Luo
Diffusion Large Language Models (dLLMs) have recently emerged as a competitive non-autoregressive paradigm due to their unique training and inference approach. However, there is cu…
Dagger Behind Smile: Fool LLMs with a Happy Ending Story
Xurui Song, Zhixin Xie, Shuo Huai +2
The wide adoption of Large Language Models (LLMs) has attracted significant attention from attacks, where adversarial prompts crafted through optimization or m…