9 papers
NetCoFi: A Budget-Aware Coarse-Fine Dual-Branch Model for Encrypted Traffic Classification
Zhengyi Ma, Qiming Yu, Chungang Lin +3
Encrypted traffic classification is critical for network management and security, but practical deployment must balance classification accuracy and inference cost. Existing models…
Shortcut in Generalization: Rethinking Evaluation Protocol for Encrypted Traffic Classification
Qiming Yu, Chungang Lin, Zhengyi Ma +4
Encrypted traffic classification is commonly evaluated under a range of experimental protocols, with classification performance reported as the primary measure. However, the report…
Unveiling Spectral Mechanisms in Training-Free LLM Text Detection
Haitong Luo, Xuying Meng, Weiyao Zhang +5
The rapid advancement of Large Language Models (LLMs) makes it increasingly difficult to distinguish human writing from machine-generated text. Training-free detection offers a sca…
Nethira: A Heterogeneity-aware Hierarchical Pre-trained Model for Network Traffic Classification
Chungang Lin, Weiyao Zhang, Haitong Luo +2
Network traffic classification is vital for network security and management. The pre-training technology has shown promise by learning general traffic representations from raw byte…
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…
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…