Machine learning (ML) has become the dominant approach for network traffic classification, achieving very high predictive performance. However, a model is only valuable if it learns semantically meani...
arXiv:2608.21874v1 Announce Type: cross
Abstract: Deep learning has achieved strong performance in encrypted traffic classification (ETC), yet its computational cost limits deployment on resource-con...
By Yuantu Luo, Jun Tao, Xiangyu Xu, Linxiao Yu, Kangying Li
The paper proposes a human-centered framework for validating the semantic soundness of machine learning models used in network traffic classification. It extends existing knowledge-generation methods by integrating data, models, explainability tools, visualizations, and expert reasoning to iteratively explore, verify, and refine model behavior and preprocessing steps. The framework is built on literature findings, benchmark analyses, XAI experience, and expert feedback, offering practical guidance for ensuring models learn trustworthy, semantically meaningful patterns rather than spurious correlations.
By Igor Cherepanov, David Sessler, Alex Ulmer, Thorsten May, J\"orn Kohlhammer
arXiv:2608.30745v1 Announce Type: new
Abstract: The widespread adoption of encrypted traffic poses severe challenges to current security situational awareness systems based on network traffic monitor...
By Ze Chen, Qiming Yu, Zijia Song, Guozheng Yang, Wei Yan
arXiv:2608. 15504v1 Announce Type: new Abstract: Encrypted traffic classification is vital for network security, yet real-world deployments are inherently sensitive to rare but high-loss errors such as misclassification of malicious traffic.
By Wumei Du, Jiarong Wen, Kaiyu Zhang, Zi Yang, Yiqin Lv, Longfei Zhang, Dong Liang, Zheng Xie
arXiv:2603.25507v2 Announce Type: replace-cross
Abstract: Network Traffic Classification (NTC) increasingly relies on data-driven models, yet its practical deployment is often constrained by limited...
By Giampaolo Bovenzi, Domenico Ciuonzo, Jonatan Krolikowski, Antonio Montieri, Alfredo Nascita, Antonio Pescap\`e, Dario Rossi