Robust Detection of Malicious Encrypted Traffic via Contrastive Learning，shen meng，北理，2025，TIFS

TrafCL: Robust Encrypted Malicious Traffic Detection via Contrastive Learning，Xiaodu Yang，信工所，2024，CIKM

PacketPatch: Practical generation and deployment of adversarial packets for byte-feature-based encrypted traffic classification，Yuwei Xu，东南大学，2026，Computers & Security

Swallow: A Transfer-Robust Website Fingerprinting Attack via Consistent Feature Learning，Meng Shen，北理，2025，CCS

CETP: A novel semi-supervised framework based on contrastive pre-training for imbalanced encrypted traffic classification，林鑫姐，信工所，2024，Computers & Security

Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation，Alessandro Finamore，华为法国，2023，arxiv

The Sweet Danger of Sugar: Debunking Representation Learning for Encrypted Traffic Classification，Yuqi Zhao，都令理工，2025，sigcomm

Multi-Scale Convolutional Neural Networks optimized by elite strategy dung beetle optimization algorithm for encrypted traffic classification，Quan Peng，杭州电子科技大学，2025，Expert Systems With Applications

Fingerprinting Obfuscated Proxy Traffic with Encapsulated TLS Handshakes，Diwen Xue，密歇根大学，2024，security

Ultimate Encrypted Traffic Feature Engineering: HTTPS Encrypted Traffic Classification Using Restored Application Data Unit Length，Zihan Chen，南方大学，2026，TDSC

Domain-Adversarial Training of Neural Networks，Yaroslav Ganin，俄罗斯，2016，ICLR

ByteDance: Let bytes perform brilliantly in multi-view encrypted traffic classification，Yuwei Xu，东南大学，2026，computer network

Cross-Environmental Website Fingerprinting，Jianfeng Li，西安交大，2025，infocom

Training with Only 1.0 ‰ Samples: Malicious Traffic Detection via Cross-Modality Feature Fusion，Chuanpu Fu，清华，2025，CCS

TOWARDS STABLE TEST-TIME ADAPTATION IN DYNAMIC WILD WORLD，Shuaicheng Niu，华南理工大学，2023，ICLR