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IEEE/ICACT20260019 Slide.18        [Big Slide]       [YouTube]	Oral Presentation
	Random Forest (RF) is selected as the final model: Achieves the best balance between detection performance and deployable latency. Maintains per-sample inference latency within SmartNIC hardware constraints. Offers higher robustness than single-tree models Why not Decision Tree (DT)? Although DT provides ultra-low latency. Its lower robustness makes it less reliable under dynamic and heterogeneous traffic patterns. Why not K-Nearest Neighbors (KNN)? Despite high accuracy. Per-sample inference latency is prohibitively high. Making it unsuitable for real-time, per-packet SmartNIC deployment.

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