146 citations · 1.1k across the 129 of their papers we have counts for
10 papers · 1 filter
SafeRedir: Prompt Embedding Redirection for Robust Unlearning in Image Generation Models
Renyang Liu, Kangjie Chen, Han Qiu +4
Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from their training data, leading to…
Backdoor Attacks against Image-to-Image Networks
Wenbo Jiang, Hongwei Li, Jiaming He +4
Recently, deep learning-based Image-to-Image (I2I) networks have become the predominant choice for I2I tasks such as image super-resolution and denoising. Despite their remarkable…
PRIME: Protect Your Videos From Malicious Editing
Guanlin Li, Shuai Yang, Jie Zhang +1
With the development of generative models, the quality of generated content keeps increasing. Recently, open-source models have made it surprisingly easy to manipulate and edit pho…
Singular Regularization with Information Bottleneck Improves Model's Adversarial Robustness
Guanlin Li, Naishan Zheng, Man Zhou +2
Adversarial examples are one of the most severe threats to deep learning models. Numerous works have been proposed to study and defend adversarial examples. However, these works la…
Boosting Black-box Attack to Deep Neural Networks with Conditional Diffusion Models
Renyang Liu, Wei Zhou, Tianwei Zhang +3
Existing black-box attacks have demonstrated promising potential in creating adversarial examples (AE) to deceive deep learning models. Most of these attacks need to handle a vast…
Warfare:Breaking the Watermark Protection of AI-Generated Content
Guanlin Li, Yifei Chen, Jie Zhang +5
AI-Generated Content (AIGC) is rapidly expanding, with services using advanced generative models to create realistic images and fluent text. Regulating such content is crucial to p…
Physical Backdoor Attacks to Lane Detection Systems in Autonomous Driving
Xingshuo Han, Guowen Xu, Yuan Zhou +3
Modern autonomous vehicles adopt state-of-the-art DNN models to interpret the sensor data and perceive the environment. However, DNN models are vulnerable to different types of adv…
Watermarking Pre-trained Encoders in Contrastive Learning
Yutong Wu, Han Qiu, Tianwei Zhang +2
Contrastive learning has become a popular technique to pre-train image encoders, which could be used to build various downstream classification models in an efficient way. This pro…
Local Black-box Adversarial Attacks: A Query Efficient Approach
Tao Xiang, Hangcheng Liu, Shangwei Guo +2
Adversarial attacks have threatened the application of deep neural networks in security-sensitive scenarios. Most existing black-box attacks fool the target model by interacting wi…
Privacy-preserving Collaborative Learning with Automatic Transformation Search
Wei Gao, Shangwei Guo, Tianwei Zhang +3
Collaborative learning has gained great popularity due to its benefit of data privacy protection: participants can jointly train a Deep Learning model without sharing their trainin…