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About this paper
Yuqing Li, Poonam Bala Nehru, Yunpeng Zhang, Danindu Gammanpilage, Xin Jin, Zeguan Wu, Junyu Liu
The authors compare quantum-fidelity-kernel and classical RBF SVMs for network-security classification, holding the data pipeline and SVM objective fixed. The quantum model raises CICIDS2017 ROC-AUC to 0.6666 ± 0.0316 from 0.6209 ± 0.0073, but results vary by dataset. A separate QOS-inspired estimate is smaller than explicit sparse storage, not measured memory or runtime, and does not always beat streaming.
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