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IEEE/ICACT20260019 Slide.20        [Big Slide]       [YouTube]	Oral Presentation
	Key Takeaways: High detection accuracy alone is insufficient for real-time intrusion detection. Per-sample inference latency and hardware feasibility determine deployability on SmartNIC platforms. Hardware-aware evaluation bridges the gap between machine learning research and real-world network security systems. Future Direction: This work establishes a SmartNIC-aware machine learning baseline for intrusion detection. Future work will focus on direct deployment and validation on programmable SmartNIC hardware.

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