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Beyond Measurement Metrics: A Human-Centered Framework for Semantic Validation of Network Traffic Classification

arXiv · AI, language, vision and robotics · article · Sep 15, 2026 · UTC

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 meaningful and trustworthy patterns rather than exploiting spurious correlations. Conventional evaluation practices predominantly assess predictive performance. Consequently, whether the model relies on semantically meaningful patterns remains unknown. To address these challenges, we adapt the knowledge generation framework for network traffic classification. The adapted framework combines data, ML mod

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