18 citations · 19 across the 9 of their papers we have counts for
6 papers · 1 filter
Heterogeneity-Oblivious Robust Federated Learning
Weiyao Zhang, Jinyang Li, Qi Song +5
Federated Learning (FL) remains highly vulnerable to poisoning attacks, especially under real-world hyper-heterogeneity, where clients differ significantly in data distributions, c…
Distillation-Enhanced Clustering Acceleration for Encrypted Traffic Classification
Ziyue Huang, Chungang Lin, Weiyao Zhang +2
Traffic classification plays a significant role in network service management. The advancement of deep learning has established pretrained models as a robust approach for this task…
SpecDetect: Simple, Fast, and Training-Free Detection of LLM-Generated Text via Spectral Analysis
Haitong Luo, Weiyao Zhang, Suhang Wang +4
The proliferation of high-quality text from Large Language Models (LLMs) demands reliable and efficient detection methods. While existing training-free approaches show promise, the…
Aligning the Spectrum: Hybrid Graph Pre-training and Prompt Tuning across Homophily and Heterophily
Haitong Luo, Suhang Wang, Weiyao Zhang +3
Graph ``pre-training and prompt-tuning'' aligns downstream tasks with pre-trained objectives to enable efficient knowledge transfer under limited supervision. However, current meth…
Versatile yet Efficient Network Traffic Analysis: Offloading Network Foundation Model to SmartNIC
Chungang Lin, Xuying Meng, Tianyu Zuo +9
Pervasive encryption makes large-scale labeling infeasible for traffic analysis, while security operations demand edge analysis to avert service degradation and further vulnerabili…
TraGe: A Generic Packet Representation for Traffic Classification Based on Header-Payload Differences
Chungang Lin, Yilong Jiang, Weiyao Zhang +3
Traffic classification has a significant impact on maintaining the Quality of Service (QoS) of the network. Since traditional methods heavily rely on feature extraction and large s…