TrafficMoE: Heterogeneity-aware Mixture of Experts for Encrypted Traffic Classification

ArXi:2603.29520v1 Announce Type: cross 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 challenges standard modeling approaches. Most existing frameworks rely on static and homogeneous pipelines that apply uniform parameter sharing and static fusion strategies across all inputs.