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cs.CR2026
Multimodal Reasoning with LLM for Encrypted Traffic Interpretation: A Benchmark
Longgang Zhang, Xiaowei Fu, Fuxiang Huang +1
Network traffic, as a key media format, is crucial for ensuring security and communications in modern internet infrastructure. While existing methods offer excellent performance, t…
cs.CR2026
Mean Masked Autoencoder with Flow-Mixing for Encrypted Traffic Classification
Xiao Liu, Xiaowei Fu, Fuxiang Huang +1
Network traffic classification using self-supervised pre-training models based on Masked Autoencoders (MAE) has demonstrated a huge potential. However, existing methods are confine…
cs.CR2026
TrafficMoE: Heterogeneity-aware Mixture of Experts for Encrypted Traffic Classification
Qing He, Xiaowei Fu, Lei Zhang
Encrypted traffic classification is a critical task for network security. While deep learning has advanced this field, the occlusion of payload semantics by encryption severely cha…