泥足巨人：破解后量子密码演化下的加密流量分类器
The Colossus with Feet of Clay: Debunking Encrypted Traffic Classifiers under PQC Evolution
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中文总结 AI 辅助
该研究针对后量子密码演化下的加密流量分类器，发现PQC会改变流量中可学习的网站信息呈现方式，使域内表现好的分类器跨域不可靠，进而提出需重视跨域鲁棒性的研究方向。
中文摘要 AI 辅助
加密流量分类器在训练与测试条件匹配时通常能达到较高准确率，默认假设部署流量遵循训练分布。TLS向後量子密码（PQC）迁移挑战了这一假设，因为混合密钥建立会在不改变应用标签的情况下重塑可观测流量。我们将这一变化视为PQC引发的协议漂移，并通过使用已部署的TLS 1.3混合-PQC组X25519MLKEM768进行闭域HTTPS网站指纹识别来研究其影响。我们构建了受控的、感知PQC的基准，配对传统（非PQC）流量与混合-PQC流量，随后在匹配域、跨域和部署比例设置下评估五种代表性分类器与侧信道表示。实验整体显示，PQC演化并未消除可学习的网站信息，反而改变了该信息在流量中的呈现方式，导致在域内表现良好的分类器和特征组合在跨密码域时失去可靠性。通过揭示匹配域评估的脆弱性，我们提供了策略指导，将跨域鲁棒性确定为研究重点，并为可靠的现实世界加密流量分类推荐感知协议的实践。代码可在该http URL获取。
英文摘要
Encrypted traffic classifiers often achieve high accuracy under matched training and testing conditions, implicitly assuming that deployment traffic follows the training distribution. TLS migration toward post-quantum cryptography (PQC) challenges this assumption because hybrid key establishment can reshape observable traffic without changing application labels. We frame this change as PQC-induced protocol drift and study its effects through closed-world HTTPS website fingerprinting using the deployed TLS~1.3 Hybrid-PQC group \texttt{\detokenize{X25519MLKEM768}}. We build a controlled, PQC-aware benchmark pairing Traditional (Non-PQC) and Hybrid-PQC traffic, then evaluate five representative classifiers and side-channel representations under matched-domain, cross-domain, and deployment-ratio settings. Collectively, the experiments show that PQC evolution does not remove learnable website information. Instead, it changes how that information appears in traffic, causing classifiers and feature combinations that perform well in-domain to lose reliability across cryptographic domains. By exposing the fragility of matched-domain evaluation, we offer strategic guidance, identify cross-domain robustness as a research priority, and recommend protocol-aware practices for dependable real-world encrypted traffic classification. The code is available at http://anonymous.4open.science/r/PQ-WF-Eval.
