{"ID":2823475,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2601.00357","arxiv_id":"2601.00357","title":"Traffic-MoE: A Sparse Foundation Model for Network Traffic Analysis","abstract":"While pre-trained large models have achieved state-of-the-art performance in network traffic analysis, their prohibitive computational costs hinder deployment in real-time, throughput-sensitive network defense environments. This work bridges the gap between advanced representation learning and practical network protection by introducing Traffic-MoE, a sparse foundation model optimized for high-efficiency real-time inference. By dynamically routing traffic tokens to a small subset of specialized experts, Traffic-MoE effectively decouples model capacity from computational overhead. Extensive evaluations across three security-oriented tasks demonstrate that Traffic-MoE achieves up to a 12.38% improvement in detection performance compared to leading dense competitors. Crucially, it delivers a 91.62% increase in throughput, reduces inference latency by 47.81%, and cuts peak GPU memory consumption by 38.72%. Beyond efficiency, Traffic-MoE exhibits superior robustness against adversarial traffic shaping and maintains high detection efficacy in few-shot scenarios, establishing a new paradigm for scalable and resilient network traffic analysis.","short_abstract":"While pre-trained large models have achieved state-of-the-art performance in network traffic analysis, their prohibitive computational costs hinder deployment in real-time, throughput-sensitive network defense environments. This work bridges the gap between advanced representation learning and practical network protect...","url_abs":"https://arxiv.org/abs/2601.00357","url_pdf":"https://arxiv.org/pdf/2601.00357v1","authors":"[\"Jiajun Zhou\",\"Changhui Sun\",\"Meng Shen\",\"Shanqing Yu\",\"Qi Xuan\"]","published":"2026-01-01T14:24:58Z","proceeding":"cs.CR","tasks":"[\"cs.CR\"]","methods":"[]","has_code":false}