Building Transparency in Deep Learning-Powered Network Traffic Classification: A Traffic-Explainer Framework

• URL: http://arxiv.org/abs/2509.18007v1
• Date: Mon, 22 Sep 2025 16:46:12 GMT
• Title: Building Transparency in Deep Learning-Powered Network Traffic Classification: A Traffic-Explainer Framework
• Authors: Riya Ponraj, Ram Durairajan, Yu Wang,
• Abstract summary: We propose Traffic-Explainer, a model-agnostic and input-perturbation-based traffic explanation framework.<n>By maximizing the mutual information between predictions on original traffic sequences, Traffic-Explainer uncovers the most influential features driving model predictions.<n>Experiments demonstrate that Traffic-Explainer improves upon existing explanation methods by approximately 42%.
• Score: 2.289837306672451
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent advancements in deep learning have significantly enhanced the performance and efficiency of traffic classification in networking systems. However, the lack of transparency in their predictions and decision-making has made network operators reluctant to deploy DL-based solutions in production networks. To tackle this challenge, we propose Traffic-Explainer, a model-agnostic and input-perturbation-based traffic explanation framework. By maximizing the mutual information between predictions on original traffic sequences and their masked counterparts, Traffic-Explainer automatically uncovers the most influential features driving model predictions. Extensive experiments demonstrate that Traffic-Explainer improves upon existing explanation methods by approximately 42%. Practically, we further apply Traffic-Explainer to identify influential features and demonstrate its enhanced transparency across three critical tasks: application classification, traffic localization, and network cartography. For the first two tasks, Traffic-Explainer identifies the most decisive bytes that drive predicted traffic applications and locations, uncovering potential vulnerabilities and privacy concerns. In network cartography, Traffic-Explainer identifies submarine cables that drive the mapping of traceroute to physical path, enabling a traceroute-informed risk analysis.

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