TDDM-Melatt: A Decoupled Memory and Diffusion Framework for Generalizable Encrypted Traffic Classification
The proposed TDDM-Melatt, a disentangled memory-based traffic classification framework with diffusion-based data augmentation, provides a new and effective technical pathway for encrypted traffic classification in real-world network environments.