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20232026
most citedNetGPT: Generative Pretrained Transformer for Network Traffic

18 citations · 19 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.NI2026

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…

cs.NI2025

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…

cs.NI2025

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…

cs.NI2025

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…

cs.NI2023★ 18 cited

NetGPT: Generative Pretrained Transformer for Network Traffic

Xuying Meng, Chungang Lin, Yequan Wang +1

All data on the Internet are transferred by network traffic, thus accurately modeling network traffic can help improve network services quality and protect data privacy. Pretrained…