6 papers
TYPO: Instruction-Dense Visual Jailbreaks against Commercial Closed-Source Image-Generation Models
Meng Xie, Li Zeng, Hangtao Zhang +4
Recent commercial image-generation models can generate high-quality images with readable text (e.g., posters, infographics, and manuals), attracting considerable attention. Yet we…
GhostPrompt: Cross-Image Adversarial Prompt for Vision-Language Models
Li Zeng, Zeyu Ye, Meng Xie +4
Vision-Language Models (VLMs) are known to be vulnerable to adversarial attacks, where subtle perturbations to images or texts induce erroneous outputs. However, most text-based at…
LHGstore: An In-Memory Learned Graph Storage for Fast Updates and Analytics
Pengpeng Qiao, Zhiwei Zhang, Xinzhou Wang +3
Various real-world applications rely on in-memory dynamic graphs that must efficiently handle frequent updates while supporting low-latency analytics on evolving structures. Achiev…
HoGS: Homophily-Oriented Graph Synthesis for Local Differentially Private GNN Training
Wen Xu, Zhetao Li, Yong Xiao +3
Graph neural networks (GNNs) have demonstrated remarkable performance in various graph-based machine learning tasks by effectively modeling high-order interactions between nodes. H…
Quark: Implementing Convolutional Neural Networks Entirely on Programmable Data Plane
Mai Zhang, Lin Cui, Xiaoquan Zhang +4
The rapid development of programmable network devices and the widespread use of machine learning (ML) in networking have facilitated efficient research into intelligent data plane…
RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization
Yuxia Sun, Huihong Chen, Jingcai Guo +3
Attributing APT (Advanced Persistent Threat) malware to their respective groups is crucial for threat intelligence and cybersecurity. However, APT adversaries often conceal their i…